Abstract
This paper reviews the literature on applications of remote sensing for monitoring soil- and crop- water status for irrigation purposes. The review is organized into two main sections: (1) sensors and platforms applied to irrigation studies and (2) remote sensing approaches for precision irrigation to estimate crop water status, evapotranspiration, infrared thermography, soil and crop characteristics methods. Recent literature reports several remote sensing (RS) approaches to monitor crop water status in the cultivated environment. Establishing the right amount of water to supply for different irrigation strategies (maximization of yield or water use efficiency (WUE)) for a large number of crops is a problem that remains unresolved. For each crop, it will be necessary to create a stronger connection between crop-water status and crop yield.
Highlights
Food is the basic and compulsory human requirement
The present review describes the role of remote sensing with respect to crop water status, its surface energy balance, the relationship between surface temperature and remotely sensed vegetation indices, and Water Use Efficiency (WUE) and evapotranspiration
The review is organized into the following main sections: (1) Sensors and platforms applied to irrigation studies; (2) Remote sensing approaches for precision irrigation for estimating crop water status, evapotranspiration, infrared thermography, and soil and crop characteristics
Summary
Food is the basic and compulsory human requirement. It is expected that limited land and inadequate water resources will negatively impact the expected increase in demand for food crops during the fifty years [1,2,3]. Pereira et al, [12] reported that the above goal is important where water is a scarce commodity (arid and semiarid regions) In these regions, it will be crucial to increase water productivity rather than maximizing crop yield. IN order to develop effective irrigation strategies, it is necessary to identify the appropriate indicators for monitoring crop water status at the farm level [27]. For these purposes, the required agricultural information may be derived from remotely sensed data [28]
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