3.3.1. SWP-CWSI Model Comparison

The relationship between the measured SWP and CWSI was modeled for all four canopy extraction methods and the two temperature calculations (Figure 8). The CWSI\_T100% values are higher than the CWSI\_T33% values per tree as expected. The R<sup>2</sup> is higher and the RMSE is lower for all of the CWSI\_T33%-based models in comparison to the CWSI\_T100% based models, regardless of extraction method, which possibly resulted from the higher variability of canopy temperature per tree with the CWSI\_T100% calculation. The intercept of the CWSI\_T100%-based models is significantly higher than CWSI-T33% for all canopy extraction methods. There is a significant difference in slope between the CWSI\_T100% based and CWSI\_T33%-based models for the 2PE and ED methods (*p* < 0.0001), while no significant difference is detected for the VS and RGB-BM methods (*p* > 0.05). The slope signifies the sensitivity of CWSI in relation to the change in measured SWP. Within the CWSI\_T100%-based models, the slopes of the 2PE and ED methods are significantly different (steeper) than the VS and RGM-BM methods (*p* < 0.0001) when each model was compared to the other models. No difference is found between the intercepts of these models. Within the CWSI\_T33%-based models, no difference is found in the slope or intercept. All eight models are significant (*p* < 0.0001), enabling the estimation of SWP based on these relationships.

**Figure 8.** Linear regression model of SWP and CWSI for the 2-pixel erosion (2PE), edge detection (ED), vegetation segmentation (VS), and RGB binary masking (RGB-BM) canopy extraction methods. Crop water status index (CWSI) with Tcanopy (◦C) calculated using the average 100% (CWSI\_T100%) (red points and lines) and the average of the coolest 33% (CWSI\_T33%) (blue points and lines) of canopy pixels. Twet = lowest 5% of canopy pixels, and Tdry = Tair + 2 ◦C. Each point represents a measurement tree (n = 15).
