ASABE Technical Library - Abstract

Abstract. Remote sensing (RS) of EvapoTranspiration (ET) models are being used in agricultural irrigation water management. These models either rely on distributed information on surface vegetation indices (visible and near infra-red bands) and/or on surface temperature (infra-red) images. RS of ET models perform better on certain regions, environments and surface conditions and thus there is a need to continue evaluating these algorithms using different RS platforms. A main challenge regarding RS imagery is that the temporal resolution of multispectral satellite images is not adequate (e.g., every 16 days in the case of Landsat 8) to estimate daily crop ET. If there are clouds during a satellite overpass then estimates of ET for a month or longer will not be possible. In addition, for some small fields, satellite spatial (pixel) resolution is too coarse. In the case of regular manned airborne RS, there is the advantage of larger temporal and spatial resolution. However, the cost of using the platform is high, most often not flexible in terms of availability during the crop growing season and time of day desired, and product delivery (processing) may take too long. Therefore, in order to have a high resolution, on demand multispectral RS platform, an integrated RS system comprised of multispectral sensors in a fix-wing small unmanned aircraft system (sUAS) was developed.

This article describes: requirements to obtain permission to operate sUAS, sensors mounted, image processing, sUAS platform, and the application of a RS of ET algorithm.