Articles
Comparison and relationship between ground and remote determination of leaf area index in wild blueberry fields
Article number
1440_34
Pages
241 – 248
Language
English
Abstract
Research and development activities using the UAV and other remote sensing devices have culminated in using remote techniques to estimate leaf area.
The objective of this study was to evaluate and establish a relationship between the destructive and non-destructive methods of measuring leaf area index (LAI) in wild blueberry fields.
Two locations were considered for this study in the 2020 growing season.
At each site, a randomized complete block experimental design with six replicates, four disease management treatments, and a plot size of 6×8 m, with a 2-m buffer between plots was used.
The DJI Matrice 300 unmanned aerial vehicle (UAV) was equipped with a 5-band (blue, green, red, red edge, and near-IR bands) multispectral Micasense camera and flown at 30 m.
Quadrant LAI measurements, remote LAI measurements, and aerial flights were conducted simultaneously.
Correlation and regression analyses were performed on the LAI data.
Results have shown a moderately strong and positive correlation and regression values (r=0.54, r2=0.29) between the Sunscan and ground measurements for LAI. Results further indicate that NDVI and VARI showed stronger correlative values with quadrant LAI, r=0.72 and 0.70 as compared to the Sunscan LAI, r=0.66 and 0.69. Therefore, the regression analysis showed that moderately low R2 values were observed for quadrant LAI when compared to Sunscan LAI values.
The moderately high correlation values obtained in this study have demonstrated the potential of using vegetative indices to estimate LAI. Therefore, NDVI and VARI can be used as predictors of LAI. In conclusion, the study has demonstrated a moderate relationship between the direct (destructive) and indirect (non-destructive) methods of determining LAI in wild blueberry fields.
However, caution should be applied to the extent and application of these values.
The objective of this study was to evaluate and establish a relationship between the destructive and non-destructive methods of measuring leaf area index (LAI) in wild blueberry fields.
Two locations were considered for this study in the 2020 growing season.
At each site, a randomized complete block experimental design with six replicates, four disease management treatments, and a plot size of 6×8 m, with a 2-m buffer between plots was used.
The DJI Matrice 300 unmanned aerial vehicle (UAV) was equipped with a 5-band (blue, green, red, red edge, and near-IR bands) multispectral Micasense camera and flown at 30 m.
Quadrant LAI measurements, remote LAI measurements, and aerial flights were conducted simultaneously.
Correlation and regression analyses were performed on the LAI data.
Results have shown a moderately strong and positive correlation and regression values (r=0.54, r2=0.29) between the Sunscan and ground measurements for LAI. Results further indicate that NDVI and VARI showed stronger correlative values with quadrant LAI, r=0.72 and 0.70 as compared to the Sunscan LAI, r=0.66 and 0.69. Therefore, the regression analysis showed that moderately low R2 values were observed for quadrant LAI when compared to Sunscan LAI values.
The moderately high correlation values obtained in this study have demonstrated the potential of using vegetative indices to estimate LAI. Therefore, NDVI and VARI can be used as predictors of LAI. In conclusion, the study has demonstrated a moderate relationship between the direct (destructive) and indirect (non-destructive) methods of determining LAI in wild blueberry fields.
However, caution should be applied to the extent and application of these values.
Publication
Authors
K.E. Anku, D.C. Percival
Keywords
normalized difference vegetative index (NDVI), visible atmosphere red index (VARI), remote sensing, vegetation index, sunscan, botrytis blight, monilinia blight
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