*5.1. Remote Sensing*

As discussed above, in irrigated agriculture, improvement of WUE is achieved by optimising the timing and quantity of irrigation applications. The scheduling methods described, whether plant-, soil- or meteorologic-based (evapotranspiration), are normally used on the ground. These methods are generally expensive, time-consuming and cannot be easily automated [16], and also mostly location-specific and not suitable for use in large areas. The option of remote sensing, which is not at all a new concept in agriculture, has, in the recent years, been an active area of irrigation water managemen<sup>t</sup> research due to its advantages in systematic measurements across space and time, ability to cover large areas and capability to be integrated into models and with Geographic Information Systems (GIS).

New approaches using remotely sensed data to estimate the crop or plant water status and hence schedule irrigations are emerging. The first is satellite imagery which has been applied in many agricultural applications, for example yield and disease monitoring. In the last few decades, methods using algorithms to derive vegetation indices from satellite imagery in combination with ground-based measurements to estimate evapotranspiration (ET) over large areas have emerged [21,28]. Use of Landsat thermal infrared (TIR, https://lta.cr.usgs.gov/L8) imagery to derive spatial variability information of ET at the field scale and uniformity of water consumption for the purposes of improving WUE [29,30] is a recent step towards improved irrigation water management.

Use of remote sensing in irrigation water use monitoring, evaluation and managemen<sup>t</sup> are underutilized due to issues of spatial and temporal resolution, quality of results and one-time/one-place syndrome among others. However, the current Lansat-8 satellite series comes with a 30 m spatial resolution and can be used to assess actual crop evapotranspiration and crop water use at the field and farm scale. There are a number of commercial satellites now available that may be used for agricultural purposes, for instance Sentinel-2 (https://sentinel.esa.int/web/sentinel/missions/ sentinel-2) and Planet (https://www.planet.com/markets/monitoring-for-precision-agriculture/).

Another remote sensing approach to determining the crop water status, which is still in research phase, is the use of thermal and multispectral imagery collected using unmanned aerial vehicles (UAV) or drones. Research has shown that the plant canopy temperature is correlated to the plant water status, and hence can be used for irrigation water managemen<sup>t</sup> [31]. Applications using reflectance of near and mid-infrared regions of the electromagnetic spectrum to assess water status in cereal crops, fruit trees, grapevine, and pasture are described in Cozzolino [31].

The main advantage of remote sensing is the ability to estimate the crop water status over spatial scales, which cannot be possibly realised with the conventional methods such as soil probes or plant-based techniques. It is also expected that, with the increased uptake of drone technology, their prices will decrease and therefore become more accessible to many farmers. However, increased effort is also needed to connect irrigators and remote sensors to maximise economies of scale. Key opportunities and advances to watch include future collection of very high resolution (<10 m) data through hyperspectral sensors such as the current commercial IKONOS and Quickbird satellites, rapid data access availability of data from multiple sensors with a wide array of spatial, spectral, and radiometric features and remote sensing multi-data synthesis through streaming technology.
