Abstract
Advancements among remote sensing technologies and platforms have provided opportunities to collect spatially continuous biophysical parameters for the benefit of precision agriculture. Specifically, unmanned aerial vehicles with mounted Light Detection and Ranging (LiDAR) sensors have promise in characterizing crop biophysical parameters, such as canopy height (CH) and leaf area index (LAI). This study aimed to demonstrate the assessment of CH and LAI using UAV LiDAR-based methodologies under varying light conditions (e.g. day or night). The methods incorporated the use of the cloth simulation filter (CSF) to assign ground/vegetation status of the LiDAR point cloud for CH calculations, and then further benefited from the inclusion of laser penetration and intensity-based LiDAR indices to estimate LAI. These methods were replicated with identical day and night flights for a multi-planting date (seven dates) corn experiments conducted in Temple, Texas. Findings suggest that both CH ( R 2 ≥0.91; RMSE ≤15.43) and LAI ( R 2 ≥0.77, RMSE =0.52) measurements are highly correlated when comparing in-situ and LiDAR-based measurements. When comparing between LiDAR data collected during day and night flights, CH showed very little difference (Δ R 2 ≤0.01) and were found to be highly replicable. LAI measures presented more differences (Δ R 2 ≤0.05) between the day and night collections that we attribute to leaf turgor due to the relatively minor differences among models. The findings within provide the foundation for future works aiming to incorporate day and/or night LiDAR-based precision agriculture.
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Claims 5
Claim · model-written summary
UAV LiDAR canopy height (CH) was highly correlated with in-situ measurements in corn (R2 at least 0.91, RMSE at most 15.43).
- Taxon
- corn
Zea mays subsp. mayse1 - Outcome
- CHe0
- Value
- R 2 ≥0.91; RMSE ≤15.43e0
- Qualifier
- highly correlatede0
- Comparator
- in-situe0
- Setting
- Temple, Texase1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“both CH ( R 2 ≥0.91; RMSE ≤15.43) and LAI ( R 2 ≥0.77, RMSE =0.52) measurements are highly correlated when comparing in-situ and LiDAR-based measurements”
e1“multi-planting date (seven dates) corn experiments conducted in Temple, Texas”
Claim · model-written summary
UAV LiDAR leaf area index (LAI) was highly correlated with in-situ measurements in corn (R2 at least 0.77, RMSE 0.52).
- Taxon
- cornZea mays subsp. mayse1
- Outcome
- LAIe0
- Value
- R 2 ≥0.77, RMSE =0.52e0
- Qualifier
- highly correlatede0
- Comparator
- in-situe0
- Setting
- Temple, Texase1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“both CH ( R 2 ≥0.91; RMSE ≤15.43) and LAI ( R 2 ≥0.77, RMSE =0.52) measurements are highly correlated when comparing in-situ and LiDAR-based measurements”
e1“multi-planting date (seven dates) corn experiments conducted in Temple, Texas”
Claim · model-written summary
Canopy height from day and night LiDAR flights differed very little (change in R2 at most 0.01) and was highly replicable.
- Taxon
- cornZea mays subsp. mayse1
- Outcome
- CHe0
- Value
- Δ R 2 ≤0.01e0
- Qualifier
- highly replicablee0
- Comparator
- day and night flightse0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“When comparing between LiDAR data collected during day and night flights, CH showed very little difference (Δ R 2 ≤0.01) and were found to be highly replicable”
e1“multi-planting date (seven dates) corn experiments conducted in Temple, Texas”
Claim · model-written summary
LAI from day and night LiDAR collections differed more than canopy height did (change in R2 at most 0.05).
- Taxon
- cornZea mays subsp. mayse1
- Outcome
- LAIe0
- Direction
- more differencese0
- Value
- Δ R 2 ≤0.05e0
- Comparator
- day and night collectionse0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“LAI measures presented more differences (Δ R 2 ≤0.05) between the day and night collections”
e1“multi-planting date (seven dates) corn experiments conducted in Temple, Texas”
Claim · model-written summary
The authors attribute the larger day-night differences in LAI to leaf turgor, given the relatively minor differences among models.
- Taxon
- cornZea mays subsp. mayse1
- Outcome
- more differencese0
- Qualifier
- leaf turgore0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“LAI measures presented more differences (Δ R 2 ≤0.05) between the day and night collections that we attribute to leaf turgor due to the relatively minor differences among models”
e1“multi-planting date (seven dates) corn experiments conducted in Temple, Texas”