A Method for Deriving Plant Temperature from UAV TIR Image

Abstract

Crops are greatly affected by the temperature of farmland surface during their growing period. It is feasible to investigate the growth status of crops based on temperature information. For serving the research of crop growth status, the component temperature (e.g. temperature of vegetation and temperature of soil) are in need to be obtained. In this study, an unmanned aerial vehicle (UAV) temperature measurement system with a thermal infrared (TIR) imager and a charge-coupled device (CCD) camera is assembled and applied to measure the brightness temperatures of farmland surface. The target areas were photographed by the UAV temperature measurement system according to a pre-set route, and obtain TIR and visible images. The component temperatures are obtained from the TIR image as following processes: (1) When shaded components are negligible at noon, two components, i.e. vegetation and soil, are divided by the OTSU algorithm; and (2) When shaded components cannot be ignored in the morning and afternoon, various components, i.e. vegetation, soil and concrete, the TIR image is divided into soil, vegetation and concrete by the corresponding classified visible images; Then, each of the components is divided into light and shaded components by the OTSU algorithm; thus, four components are obtained, including sunlit vegetation, shaded vegetation, sunlit soil, and shaded soil. The derived component temperatures can serve as inputs to agricultural and water resource models.