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ABSTRACT
Landsat-9 Panchromatic (PAN) band images are 7 times finer than land surface temperature (LST) photos of the Thermal Infrared (TIR) band. PAN bands have superior image resolution, consistency, and less ambiguity than TIR bands due to their smaller pixel sizes. Image fusion enhances images by combining data from several sources to make them better. Image fusion methods cannot combine PAN and TIR bands. This research proposes Fourier Transformation-based fusion (FTBF) to merge PAN and TIR band data to spatially enhance Landsat-9 LST images from 100 m to 15 m resolution. Fourier transformation integrates frequency domain filtering and spatial matching in FTBF. In-situ infrared thermometers data loggers verified temperature and picture quality parameters for FTBF algorithm fused image thermal points. Comparing downscaled LST with ground truth points yielded an RMSE of 0.18 and a correlation of 0.93. Eight qualitative and quantitative characteristics reveal that FTBF fusion methods improve TIR picture spatial resolution and preserve original LST data thermal attributes. LST-Pan fusion can detect surface temperature change for land-use change, fire detection, forest fire, agricultural analysis, crop management, and flood mapping at finer scales.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The datasets generated during the current study are available from the corresponding author on reasonable request.
Declaration Statements
Conflict of Interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.