**3. Results**

Table 3 shows the performance of the separate Sentinel-2 bands and VIs for LAI estimation of cotton, tomato, and wheat. Overall, the bands that modelled LAI best were Band-7 (Red edge-3), Band-9 (Water vapor), and two NIR bands (8 and 8A). Notably, Band-8A (Narrow NIR) showed a higher correlation with LAI and lower RMSE in LAI estimation than Band-8 (NIR) in all three crops. Consequently, NDVI8A performed better than NDVI. Importantly, Band-4 (Red) showed average performance, and Band-5 (Red edge-1) showed weak performance relative to other bands in tomato and cotton. Therefore VIs based on the better performing bands might be beneficial for LAI estimation. One such VI, namely reNDVI, showed a very high estimation performance. Finally, the high performance in LAI prediction by the Water vapor Band-9 suggests that this band might be useful for creating VIs with good correlation to LAI. This result was confirmed by low RMSE and high R<sup>2</sup> values of the new WEVI and WNEVI that are based on Band-9. The two new VIs proposed in the study (WEVI and WNEVI) alongside reNDVI showed superior performance in LAI predictions compared to NDVI and NDVI8A in all three crops, with the largest difference in wheat.


**Table 3.** Performance of Sentinel-2 bands and VIs used in the present study. The performance of best performing bands and VIs for each crop are in bold.

Figure 3 shows the reflectance in each band and the corresponding LAI measurements in this study's experiments. The reflectance in bands 1, 2, 3, 4, 5, 11, 12 in cotton and processing tomatoes start saturating from LAI ≈ 3 and almost no longer changing at LAI ≈ 6. This result is especially important because bands 4 and 5 are used in many VIs. On the other hand, bands 6, 7, 8, 8A, 9 were not saturated. Insufficient satellite imagery and field measurements of LAI were acquired during the wheat experiments and hindered estimating the saturation levels of this crop.

**Figure 3.** Band reflectance and LAI measurements in the following experiments: (**A**) Wheat Saad, (**B**) Wheat Yavne, (**C**) Cotton Megido (centre of field), (**D**) Tomato Gadash 2019, (**E**) Tomato Gadot 2019, (**F**) Tomato Gadot 2020.

Figure 4 shows the RMSE of Sentinel-2 bands LAI estimation for wheat, cotton, and tomato. While the RMSE of Sentinel-2 bands most commonly used in VIs formulae (bands 2-8A) in wheat LAI estimation is closer to each other, Band-4 and Band-5 have notably high RMSE in cotton and tomato LAI estimation, and this is especially pronounced for Band-5 in tomato.

**Figure 4.** RMSE of Sentinel-2 bands in tomato, cotton, and wheat LAI estimation.

Figure 5 shows reNDVI, WEVI, WNEVI, NDVI, and MTCI linear regression models for tomato, cotton, and wheat.

Figure 6 shows the LAI measurements and LAI estimation based on the VIs used in this study using the models described in Table 3. While several VIs showed similar behavior in LAI estimation, MTCI, MSAVI, reNDVI, WEVI, and WNEVI were notably different. MTCI, affected by the low performance of the Band-5, did not perform well in tomato LAI estimation in Gadot 2019 and 2020. MSAVI notably underestimated wheat LAI values. Conversely, reNDVI, WEVI, and WNEVI show closer resemblance to measured LAI than all other VIs. In the present study, no difference in the spectral response of Sentinel-2A and -B satellites was observed owing to an excellent radiometric cross-calibration of the MSI on both satellites.

**Figure 5.** *Cont*.

**Figure 5.** Tomato, cotton, and wheat LAI-VI linear regression models: (**A**) Tomato reNDVI; (**B**) Tomato WEVI; (**C**) Tomato WNEVI; (**D**) Tomato NDVI; (**E**) Tomato MTCI; (**F**) Cotton reNDVI; (**G**) Cotton WEVI; (**H**) Cotton WNEVI; (**I**) Cotton NDVI; (**J**) Cotton MTCI; (**K**) Wheat reNDVI; (**L**) Wheat WEVI; (**M**) Wheat WNEVI; (**N**) Wheat NDVI; (**O**) Wheat MTCI. The data used to derive the models is presented in Table 2, the RMSE values of the models are given in Table 3.

**Figure 6.** *Cont*.

**Figure 6.** LAI measurements and LAI estimation based on the VIs used in the present study in the following experiments: (**A**) Wheat Saad, (**B**) Wheat Yavne, (**C**) Cotton Megido (centre of the field), (**D**) Tomato Gadash 2019, (**E**) Tomato Gadot 2019, (**F**) Tomato Gadot 2020.
