Calculating High Resolution CWSI Maps for Entire Growing Season of a Cultivated Barley Field with UAV-Collected Surface Temperatures.

Abstract:

With agriculture as the largest consumer of freshwater and an overall increasing pressure on water resources, developing more efficient irrigation systems is important. Combining the crop water stress index (CWSI) with unmanned aerial vehicles (UAVs) enables detection of which specific areas within a cultivated field that requires irrigation to ensure healthy growing plants. In this study remotely sensed, high resolution surface temperatures are collected with a thermal camera onboard an UAV. Temperatures are used to calculate spatially distributed, high resolution CWSI maps over a barley field during growing seasons 2014 and 2015. In early stages of the barley growing season, surface temperatures are an ensemble of both soil and canopy temperatures. Canopy temperatures are extracted using leaf area index and the two source energy balance modelling scheme. This approach enables CWSI calculations for homogeneous and evenly distributed crops (such as barley) during early as well as late stages of a growing season. CWSI maps are calculated using both an empirical and an analytical approach and are compared and validated against modelled canopy conductance and transpiration rates.