# Remote Sensing for Irrigation of Horticultural Crops
## 4 Approaches to Precision Irrigation
### Infrared Thermography
#### 4.2.1 Cwsi
They tested CWSI for scheduling irrigation for watermelon grown with five irrigation treatments (0%, 25%, 50%, 75%, and 100%) in terms of the replenishment of the water depletion (0.90 m soil profile depth). The CWSI was calculated from IR canopy temperatures, air temperatures, and vapor pressure deficit values. In two years, the fully irrigated treatment gave the highest yield and water use. The CWSI values tended to be consistent with the soil water content. The authors proposed a linear equation of CWSI versus yield prediction, and suggested testing in long-term experiments a critical value of CWSI at which a farmer should irrigate. Recently, [PERSON] et al. [172] measured the CWSI in three peach cultivars (_Prunus persica_ L.) throughout different growing seasons. They measured the canopy temperature of well-watered trees using high-resolution thermal imagery obtained from an airborne platform and related it to leaf water potential (\(\psi_{\text{L}}\)) as a water stress indicator. Results demonstrated that (i) the CWSI had similar seasonal responses and (ii) a common \"non-water-stressed baseline\" can be used during the course of the entire crop season. The CWSI is a practical method for evaluating the spatial variability of peach tree water status in heterogeneous orchards, and for deriving \(\psi_{\text{L}}\) maps throughout a complete growing season. [PERSON] et al. [173] evaluated the ability of high-resolution UAV-based thermal imaging to estimate instantaneous and seasonal variability of plant water status within a vineyard. CWSI correlated well with \(\psi\)s and \(\text{g}_{\text{s}}\) at the moment of image acquisition, showing great potential for monitoring instantaneous variations in water status, but it did not provide a good estimation of variations of plant water status on a single day. The results added evidence regarding the suitability of this approach, and reinforced the potential role UAV thermal imaging may have as an instantaneous water-stress mapping tool. Similarly, [PERSON] et al. [174] conducted an airborne study over a vineyard, with the goal of computing image-derived spectral and thermal indices, and indicators of water status in vines including (i) the crop water stress index (CWSI), stomatal conductance index (Ig) [164] and (ii) a formulation of the stomatal conductance index (I3) [164]. They concluded that the relationship between thermal imagery and derived indices can be considered as a short-term response, a kind of instantaneous \"picture\" of the plant water status situation, while spectral vegetation indices are probably the result of cumulative water deficits. [PERSON] et al. [84] validated a methodology for producing high-resolution maps of canopy conductance and CWSI, potentially useful for calculating actual ET and as an input for scheduling irrigation. The canopy of conductance and CWSI maps of olive orchards were acquired by airborne and UAV platforms for two years with different irrigation treatments. [PERSON] et al. [175] showed that the CWSI measured in the first afternoon hours were a good tool for identifying seasonal changes in the water status of a pistachio orchard submitted to variable water stress by regulated deficit irrigation practices. The temperature of pistachio trees showed great responsiveness to variations in plant water status. [PERSON] et al. (2015) analyzed ET and CWSI in tomato confirming that the use of infrared thermometry to calculate the CWSI is a reliable technique for scheduling irrigation using the determined upper and lower CWSI baselines in a husk tomato crop. The CWSI value increased until it reached 0.7 in the treatment with severe irrigation restrictions (40% ET\({}_{\text{o}}\)). [PERSON] et al. (2016) used UAV systems to derive CWSI from high-resolution thermal imagery. They assessed the spatial variability of crop water status in a pistachio orchard for precision irrigation purposes.