A Modified Single-Channel Algorithm for Estimating Land Surface Temperature from UAV TIR Imagery
- Resource Type
- Conference
- Authors
- Wei, Letian; Wu, Hua; Jiang, Xiao-Guang; Ru, Chen; Jiang, Ya-Zhen; Gao, Cai-Xia
- Source
- 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Geoscience and Remote Sensing Symposium IGARSS , 2021 IEEE International. :8185-8188 Jul, 2021
- Subject
- Aerospace
Geoscience
Photonics and Electrooptics
Signal Processing and Analysis
Temperature sensors
Temperature measurement
Urban areas
Land surface
Unmanned aerial vehicles
Land surface temperature
Reliability
Unmanned aerial vehicle (UAV)
Thermal Infrared (TIR)
Land surface temperature (LST)
Atmospheric parameters
Emissivity
- Language
- ISSN
- 2153-7003
Thermal Infrared (TIR) cameras mounted on unmanned aerial vehicles (UAVs) provide low-cost, high spatial and temporal resolutions TIR data. This paper develops a novel single-channel algorithm adaptive to UAV TIR data. Atmospheric parameters were estimated using atmospheric reanalysis data and surface emissivity were acquired by the Portable Fourier transform thermal infrared spectrometer (102F). Then the effective atmospheric transmittance and emissivity were calculated owing to the broad spectral range of the UAV TIR channel. The results were validated using in-situ land surface temperature (LST) derived from SI-111 radiometers at an area of Baotou City, China. The root mean square error (RMSE) were 2.31K on 24 September and 1.82K on 26 September, which indicates that the proposed algorithm is a promising method to estimate LST from UAV TIR images.