# Remote Sensing for Irrigation of Horticultural Crops
## 4 Approaches to Precision Irrigation
### ET Estimation
[120] have combined METRIC-derived estimates of ET with a water balance model named LORMOD [128] to evaluate, at a plot level, the use of near-real time ET estimates to update and correct irrigation scheduling predictions and to assess its impact on WUE. ET estimates derived from satellites were used in a daily soil-water-balance model to improve accuracy of field-by-field ET demands and, as a consequence, field-scale irrigation schedules. This approach combined high spatial resolution (satellite RS) data with high temporal resolution data (daily soil-water-balance), providing significant advances in irrigation schedules, as reported for cotton (a 24% reduction) increasing field irrigation efficiency to 0.72; the field irrigation efficiency reached 0.90 for sugar beet [120]. [PERSON] et al. [129] reported an estimation of actual ET for central New Mexico. They matched ET images derived from MODIS with those taken by Landsat. The adoption of a METRIC model based on MODIS imageries produced monthly and annual ET estimates, comparable to those obtained with Landsat imagery. [PERSON] and [PERSON] [130] reported a ReSET model based on wind from multiple weather stations and the use of a weather station for the model calibration. This flexible approach generated raster interpolated weather parameters, accounting for spatial variation of weather parameters between weather stations, which can be significant. They found that ET calculated using this approach could vary by 17% compared with ET calculated with point values. Subsequently, [PERSON] and [PERSON] [131] assessed the use of actual ET calculated by ReSET to estimate seasonal crop water use at regional scale instead of the traditional ET estimation method based on reference ET and crop coefficients. [PERSON] et al. [132] estimated the energy balance components over a drip-irrigated olive orchard, using thermal and multispectral cameras placed on a helicopter-based unmanned aerial vehicle, acquiring high-resolution images to assess intra-field spatial variability. In the field of irrigation scheduling/WUE, there are very few concrete outcomes. In particular, [PERSON] et al. [133] analyzed, from the PLEIADeS framework, five agricultural systems, in a broad range of arid and semi-arid conditions characteristic for the European, Southern Mediterranean, and American regions. The aim of the project was to improve the efficiency of the irrigation schemes, made possible through wide space-time coverage of Earth Observation data and interactive networking capabilities of Information and Communication Technologies. They included the following: canopy parameters, fractional vegetation cover, LAI, albedo, crop coefficients, potential ET, irrigation water requirements. They confirmed the possibility of estimating crop coefficient from NDVI, relying upon advances in spatial and radiometric accuracy of new sensors (e.g., Sentinel-2), for a full exploitation of their applications. [PERSON] et al. [107] quantified irrigation water use and water provenance (surface water or groundwater), combining t remote sensing data on irrigation dynamics and actual ET linked with a river-reach hydrological model. They concluded that the results were as accurate as those of more traditional irrigation area modelling using remotely sensed irrigated areas. Actual ET data can be used to understand irrigation dynamics, the constraints in irrigation models, and specific areas that require better monitoring. [PERSON] et al. [134] estimated the ET and crop coefficients of table grape vineyards trained on overhead \"tendone\" systems in the Apulia region (Italy). The FAO direct methodology for estimating potential evapotranspiration (ETp) was used to estimate maximum vineyard transpiration. The model, based on existing validated methodologies, used appropriate values of canopy variables (albedo and the LAI) derived by means of multispectral satellite data.