Maize evapotranspiration estimates using planet dove mini-satellites and field-level infrared thermometers

Water scarcity, climate change, and the need to sustain irrigated agriculture demand improved methods to manage irrigation water. Irrigation scheduling can be improved when remote sensing (RS) images are used because RS captures the actual crop field conditions. Mini -satellites (mS) are small spaceborne RS platforms that can provide high spatial and temporal resolution multispectral (MS) images. These multispectral images can be used to estimate maize actual evapotranspiration (ETa) on a daily basis. Thus, the main objective of this study was to assess the accuracy of maize ETa estimates when mS MS images were used in two different ETa algorithms. This study was conducted at two research sites in northern Colorado, USA. A reflectance -based crop coefficient and a one -source surface energy balance (OSSEB) models were applied, using MS Planet Dove images, to map maize ETa. An Eddy Covariance energy balance system was used to assess the accuracy of distributed ETa estimates. Results indicate that the reflectance -based crop coefficient method can be used with mS MS images yielding acceptable estimates. Both ETa models performed better in the case of the sub -surface irrigated maize. Further, OSSEB-based estimates of ETa model were more accurate over the surface irrigated maize and homogeneous soils; when surface reflectance images were paired with radiometric surface temperature data from groundbased infrared thermometers. These results imply that potentially maize ETa could be mapped, on a daily basis with good accuracy, using Planet Dove mS-based MS reflectance images and ground -based radiometric surface temperatures.