10.6084/m9.figshare.4538105.v1 Susan Meerdink Susan Meerdink Spectral emissivity features of plants: Prospects for the Hyperspectral Thermal Emission Spectrometer (HyTES) sensor figshare 2017 thermal spectroscopy remote sensing plant species Botany Plant Biology Ecology 2017-01-10 23:29:11 Poster https://figshare.com/articles/poster/Spectral_emissivity_features_of_plants_Prospects_for_the_Hyperspectral_Thermal_Emission_Spectrometer_HyTES_sensor/4538105 <div><b>Presented at the 2016 Annual Fall AGU Meeting</b></div><div><b><br></b></div>The Thermal Infrared (TIR) spectrum has not been widely adopted for vegetation studies due to the limited availability of TIR sensors, low signal to noise ratios, and subtle features of plant spectra. However, recent improvements in TIR sensor design, atmospheric correction, and temperature emissivity separation have begun to achieve the necessary data quality for discerning TIR spectral features in plants. These technical developments make it possible to re-examine the TIR emissivity characteristics of plants. The Hyperspectral Thermal Emission Spectrometer (HyTES) airborne sensor has 256 bands that measures radiance between 7.5 - 12 μm and can be used to retrieve spectral emissivity with high precision. Here we evaluate: 1) TIR spectral variation between plant species at leaf scale; 2) TIR spectral signatures of plant canopies using HyTES imagery; and 3) TIR spectra scaling capabilities from leaf to canopy. HyTES imagery was acquired over Huntington Gardens in Pasadena, California, US on 1/25/2016 with a spatial resolution of 2 m. Leaf samples were collected on 2/2/16 from a diversity of trees species that had canopies larger than 10 m in diameter. Leaf spectra were collected using a Nicolet Model 4700 Interferometer Spectrometer fitted with a Labsphere gold coated integrating sphere which measured emissivity from 2.5 – 15.4 μm. While plant features are subtler and have lower reflectance in the TIR than the visible shortwave infrared spectrum, plants showed considerable spectral diversity at the leaf and canopy level using HyTES imagery. These analyses support the first steps of using HyTES imagery for future remote sensing vegetation studies.