## 2 Materials and Methods
### Image Acquisition and Processing  
Throughout the growing season, a total of four drone flights were conducted, with two flights in each of the selected orchards, in order to gather comprehensive multispectral and thermal imaging data. The initial flight was conducted on 24 th June (DOY 175, Flight 1), capturing images during the growth stages of the pistachio nuts (F1-F2 stages), corresponding to when the mesocarp started to turn yellow, while the subsequent flight took place on 7 th September (DOY 275, Flight 2), providing valuable information on the progression of plant growth and nut maturity during the later stages of the season (M stage). All flights were planned and executed automatically at 30 m above the ground level and 2 m/s speed, under optimal weather conditions, on windless and sunny days with minimal cloud cover (1 okta cloud conditions). This settings delivered a ground resolution of 1.29 cm/pixel for the thermal and the multispectral imagery. The UAS system (Figure 3) employed for data acquisition was composed of a UAV DJI Inspire 2 (DJI, Shenzhen, Guangdong, China, Table 1), which was equipped with a Micasense ALTUM multispectral camera (AgEagle Sensor Systems Inc., Wichita, KS, USA, Table 2). Figure 3: UAS system model employed for data acquisition. (**a**) UAV DJI Inspire 2 drone. (**b**) Micasense ALTUM multispectral camera. (**c**) UAS flying over the pistachio orchard. Moreover, to ensure enhanced geometric accuracy during the image mosaicking process, a set of five ground control points (GCPs) was employed, positioned in the field utilizing a highly precise JAVAD Triumph-2 real-time kinematic (RTK) GNSS system. The acquired images were processed using Agisoft Metashape Professional software (v1.7.6, Agisoft LLC, St. Petersburg, Russia), adhering to the manufacturer's recommended guidelines. Initially, ground control points (GCPs) were identified within the images to optimize camera positions, orientation data, and enhance orthophoto accuracy. Subsequently, calibrated reflectance panel images were located to adjust image data based on the reflectance values supplied by Micasense. A high-quality dense point cloud was then generated, preserving the original resolution of the raw images without downscaling. A digital surface model (DSM) was created using the comprehensive dense point cloud. This was followed by the automatic classification of ground points, which relied exclusively on these points to generate the digital terrain model (DTM). Then, these two layers were employed to calculate the canopy height model (CHM) in order to distinguish the pistachio tree crowns from the background. A total of four orthophotos with six spectral bands were created from these flights and they were subsequently used to calculate a range of the VIs (Table 3), offering valuable insights into the vigor and overall productivity of the pistachio plants under investigation. These indices can aid in identifying the status of the vegetation and patterns and trends in plant growth [19; 39], as well as detecting potential issues related to water stress, nutrient deficiencies, or disease [40; 41; 42; 43]. The calculation of the CWSI, the thermal-based VI calcu \begin{table}
\begin{tabular}{c c} \hline
**Maximum Take-off Weight and Maximum Speed** & 9.37 lbs (4250 g), 58 mph (94 kph) \\ \hline
**GPS Hovering Accuracy** & \(\pm\)1.64 feet (0.5 m) vertically, \(\pm\)4.92 feet (1.5 m) horizontally \\ \hline
**Maximum Flight Time** & Approximately 27 min \\ \hline
**Remote Controller Model** & GL6D10A \\ \hline
**Operating Frequencies** & 2.400–2.483 GHz, 5.725–5.850 GHz \\ \hline
**Maximum Transmitting Distance** & 2.2 miles (3.5 km) under CE regulations \\ \hline
**Battery Capacity, Voltage, Capacity, Power** & Model TB50, 4280 mAh, 22.8 V, 97.58 Wh, 180 W \\ \hline \end{tabular}
\end{table} 
Table 1: Detailed technical specifications of DJI Inspire 2 drone.