correcTIR: A python package and graphical user interface for processing near-surface thermal infrared data

Canopy temperature is a key indicator of plant physiological function and influences ecosystem-scale carbon and water fluxes. Near-surface thermal infrared (TIR) sensors provide a non-invasive and scalable way to measure canopy temperature with high spatial and temporal resolution. However, raw TIR readings do not directly reflect true target temperatures due to atmospheric contribution and attenuation, reflected radiation, and variations in target emissivity. Current processing approaches vary widely and often rely on proprietary software, limiting comparability and leading to inaccurate temperature estimates. To address these challenges, we introduce correcTIR, an open-source Python package and graphical user interface designed to provide a complete, standardized solution for near-surface TIR data processing. correcTIR dynamically corrects for all major sources of interference, is not tied to any specific instrument or manufacturer, and supports both image-based data (e.g., thermal imagery in .tiff format) and point-based measurements (e.g., tabular .csv files). This paper describes the physical principles behind the correction process, outlines key software functionalities, and demonstrates its application through a case study. By providing a transparent, user-friendly, and flexible framework, correcTIR enables broader, more accurate, and more comparable use of canopy temperature measurements in ecological research.