Fig 1.
The false color composite image (NIR/red/green band) of the study area derived from the Compact Airborne Spectrographic Imager (CASI) hyperspectral image and the sampling plots (green squares in the image).
Table 1.
LiDAR metrics used for maize fPAR estimation.
Table 2.
Hyperspectral metrics used for maize fPAR estimation.
Fig 2.
Pearson correlation coefficient (R) of each LiDAR metric and field-measured fPAR data.
Table 3.
Results of the multiple stepwise linear regression using LiDAR metrics.
Fig 3.
Pearson correlation coefficient (R) of each selected hyperspectral metric and field-measured fPAR.
Table 4.
Results of the multiple stepwise linear regression using hyperspectral metrics.
Table 5.
Results of the multiple stepwise linear regression using both LiDAR and hyperspectral metrics.
Fig 4.
Scatterplots of fPAR and (a) fcoverintensity, and (b) CNRH from the 25 modeling plots.
Fig 5.
Scatterplots of field-measured fPAR values versus fPAR values predicted by the LiDAR model.
Fig 6.
The scatterplots of fPAR and (a) DCI and (b) VOG2 from the 25 modeling plots.
Fig 7.
Scatterplots of field-measured fPAR versus fPAR predicted by the hyperspectral model.
Fig 8.
Scatterplots of field-measured fPAR values versus the fPAR values predicted from the combination model.