Estimation of crop latent heat flux from high resolution thermal imagery

Yan Zhu; Keith A. Cherkauer

doi:10.1117/12.2519216

14 May 2019 Estimation of crop latent heat flux from high resolution thermal imagery

Yan Zhu, Keith A. Cherkauer

Proceedings Volume 11008, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping IV; 1100803 (2019) https://doi.org/10.1117/12.2519216
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

We introduce a method to calculate evapotranspiration (ET) for individual plots in agricultural fields using the TSEB (Two-Source Energy Balance) model for high resolution thermal data from a UAS (unmanned aerial system). The model was developed for satellite remote sensing which has coarser spatial and temporal resolution. With the emergence of UAS remote sensing, this model needs to be adapted to be applied to the significantly higher resolution imagery. The average resolution of our thermal dataset is about 5 cm, which means we have multiple temperature measurements for a single plant, as opposed to satellite imagery which often views entire fields. The image resolution also means that soil contributes to overall temperature for certain pixels as well. A new algorithm is developed to classify pixels into 3 categories: soil, plant and mixture of soil and plant. Temperature distributions of plants are established and with other inputs like solar radiation, wind speed, plant height, we estimate ET distributions. Distributions of ET are acquired for the targeted plots in multiple images, and are evaluated versus stomatal conductance measurements from a steady state porometer.

Conference Presentation

Citation Download Citation

Yan Zhu and Keith A. Cherkauer "Estimation of crop latent heat flux from high resolution thermal imagery", Proc. SPIE 11008, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping IV, 1100803 (14 May 2019); https://doi.org/10.1117/12.2519216

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