# Remote Sensing for Irrigation of Horticultural Crops
## 4 Approaches to Precision Irrigation
### ET Estimation
\begin{table}
\begin{tabular}{c p{341.4 pt}} \hline \hline
1 & Scheduling irrigation to replace ET estimated from a reference ET (ETo), calculated from local weather data, which is multiplied by a crop coefficient estimated with a crop coefficient function, Kc (NDVI), where NDVI is the normalized difference vegetative index (NDVI) or a similar index adjusted for reflectance from soil. The NDVI is based on canopy irradiance in the red and near-infrared bands, which can be remotely sensed. \\ \hline
2 & Scheduling irrigation at a fixed amount of water whenever a trigger to irrigate is generated by the crop water stress index (CWSI), which is estimated using remotely sensed surface temperature (Ts) and local weather data. \\ \hline
3 & Scheduling irrigation at a fixed amount when triggered by the time-temperature threshold index (TTTI) reaching a crop and region-specific value. The TTTI is calculated using Ts. \\ \hline
4 & Scheduling irrigation to replace ET estimated with the field surface energy balance (FSEB), which uses remotely sensed surface temperature, Ts, determined from thermal infrared data, and data on canopy cover and surface emissivity deduced from the near-infrared (NIR) and visible bands. \\ \hline
5 & Sensing of crop and soil characteristics in order to guide timing, placement, and amount of fertilizer and water through irrigation (or fertigation) systems of various orders of precision. The characteristics, including crop cover fraction, nitrogen status of leaves, disease, and pest damage, all of which vary spatially and temporally, are inferred from various remotely sensed vegetative indices. \\ \hline  & [PERSON] proposed an electronic hardware and software system that acquires data from sensors and controls the operation of other hardware to pilot irrigation. This Supervisory control and data acquisition system (SCADA) acquires in situ, remotely sensed, or near-surface remotely sensed crop, soil, and micrometeorological properties as inputs for a decision-making algorithm. The system applies defined amounts of water at defined times automatically through control of an integrated irrigation application system. \\ \hline  & [PERSON] proposed an electronic hardware and software system that acquires data from sensors and controls the operation of other hardware to pilot irrigation. This Supervisory control and data acquisition system (SCADA) acquires in situ, remotely sensed, or near-surface remotely sensed crop, soil, and micrometeorological properties as inputs for a decision-making algorithm. The system applies defined amounts of water at defined times automatically through control of an integrated irrigation application system. \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Five major approaches to irrigation management using remote sensing. From [PERSON] [115]. the actual crop coefficient [124]. [PERSON] et al. [122] reported this method (Crop ET estimations based on \(\text{Kc}_{\text{act}}\)) is a useful tool for field and regional water management. The energy-balance approach has the benefit that it can be utilized to quantify the dimensions of irrigated fields and their water-use dynamics, without reference to source of water as opposed to a water balance model. This latter model necessitates the information of both the magnitude and temporal distribution of rainfall and irrigation applied to fields [125]. Temperature-based methods, as SEBAL, can be automated and likely outperform vegetation-based methods in irrigated areas, especially under conditions of low vegetation cover and high soil evaporation. According to [PERSON] et al. [126], an automated SEBAL can estimate the evaporative fraction from irrigated crops with a mean error of 14% of Rn (range 218% to 124%). [PERSON] et al. [127] confirmed the maturing technology of SEBAL and METRIC for deriving a satellite-driven surface energy balance for estimating ET from the ground's surface. The authors foresee a great future for these models in the scientific groups dealing with water resources. [PERSON] et al.