# Remote Sensing for Irrigation of Horticultural Crops
## 4 Approaches to Precision Irrigation
### Infrared Thermography
#### 4.2.1 Cwsi
The authors estimated a possible reduction of irrigation costs moving from common irrigation system to a variable rate irrigation system ([PERSON] et al., 2016). [PERSON] et al. (2016) also used IR imagery taken by UAVs to evaluate the variability in the water status of five fruit tree species. They compared the daily differential between T\({}_{\text{c}}-\text{T}_{\text{a}}\) (canopy and air temperature) with the tree water status. Since the slope of the differential with time was highly correlated with water status, the authors proposed the slope as an indicator of the stomatal behavior. An empirical approach was used to define the upper and lower limits of T\({}_{\text{c}}-\text{T}_{\text{a}}\); CWSI was calculated using the temperature data from a 13-h flight. Another important contribution of the paper was the assessment of variability in the water status based on the differences in relative canopy temperatures. The authors concluded that their approach (i) was worthwhile for managing precision irrigation; (ii) could identify water stressed areas; and (iii) could define threshold CWSI values, a great help for farmers and for irrigation strategies at different phenological stages. [PERSON] et al. (2017) analyzed the CWSI of red pepper irrigated with two systems (drip and furrow) and with different irrigation regimes. The authors concluded that CWSI could measure crop water status and improve irrigation scheduling. For high-quality yields, the authors suggested CSWI values of 0.26 for drip irrigation and 0.38 for furrow irrigation. For both irrigation methods, linear relations were found between CWSI and red pepper yield. [PERSON] et al. (2018) tested CWSI for analyzing the changes in water status of olive trees when entering into and recovering from stress on a diurnal scale. CWSI was tested in an empirical form and in two analytical configurations. The results showed that the empirical CWSI was capable even given its limitations, while the analytical forms of CWSI needed enhancement for monitoring the water status of olive. The authors proposed calculating the wet temperature analytically and fixing the dry temperature at a level of 5 \({}^{\circ}\)C higher than the air temperature. Thermal imaging and water status measurements were recorded between 12:00 and 14:00. [PERSON] et al. (2018) conducted a two-year experiment on early-ripening peach exposed to postharvest deficit irrigation schemes, concluding that IR measurements might estimate plant water stress, particularly in high-radiative arid and semi-arid climates. They found that the temperature differences (infrared-canopy temperature and air temperature) where correlated to stem water potential and proved to be a useful tool for water stress assessment for managing regulated deficit irrigation. Temperature differences (midday canopy to air temperature) ranged from 5 to 7 \({}^{\circ}\)C in the water-stressed postharvest deficit irrigation treatments, while they ranged from 1.4 to 2 \({}^{\circ}\)C in the non-water-stressed control treatments. [PERSON] et al. (2018) calculated CWSI for four 1-hour periods, ranging from 10:00 to 14:00, each day for 29 days. The estimated CWSI was smallest from 10:00 to 11:00 and largest from 12:00 to 13:00. These values may be used for precise (amounts and timing) irrigation scheduling. When measurements were taken during earlier hours, the authors suggested adopting a conservative threshold value of CWSI; in contrast, they suggested higher levels when measurements were recorded one hour after solar noon. [PERSON] et al. (2018) conducted a study using thermal data to monitor crop-water status in irrigated Mediterranean viticulture. They found that CWSI and IG might provide more meaningful information about the crop-water status than T\({}_{\text{canopy-air}}\). The authors also found that T\({}_{\text{C}}\) was significantly correlated with \(\mathrm{g_{s}}\) and net assimilation, suggesting that it can be used as a simpler parameter to support thermal remote sensing of water stress in grapevines. [PERSON] et al.