Temperature separation via eliminating shadow-pixel influence based on high-resolution sUAS image in California vineyards

The images generated by high-resolution spectral and thermal sensors equipped on small unmanned aerial vehicles (sUAV) make possible estimation of energy flux for California vineyards via the two-source energy balance (TSEB) model. Temperature (thermal) image plays an important role in the TSEB model, and the high-resolution provides an opportunity for temperature separation, which may better delineate the energy flux between canopy and soil. However, with the exception of shadow effects, outliers are another major concern during data processing with a previous temperature separation algorithm that uses the relationship between the normalized difference vegetation index (NDVI) and the corresponding temperature pixel for temperature separation. An upgraded algorithm for temperature separation was introduced in the paper titled “The suitability of the TSEB model as a tool to estimate ET partitioning using improved LAI considering the difference of climate, soil, vine variety, and seasons for research areas across California,” and this research provides example data and the upgraded algorithm (a python programmed function) to demonstrate how we finished the temperature separation process.