Striewski, FriedrichComi, Ennio LuigiTiefenbacher, FionaLack, NatalieBattaglia, MattiaBleisch, SusanneDutta, SoumyaFeige, KathrinRink, KarstenNsonga, Baldwin2024-05-212024-05-212024978-3-03868-260-8https://doi.org/10.2312/envirvis.20241135https://diglib.eg.org/handle/10.2312/envirvis20241135High resolution thermal infrared (TIR) remote sensing in the urban environment for building insulation inspection requires careful consideration of atmospheric and ground-located factors on the radiometric signal, with one being the microclimatic variability within the scene. Based on the assumption of roads as pseudo invariant objects, the TURN algorithm represents a tool to interpolate local temperature deviation within a scene and to normalize TIR-imagery in order to obtain a microclimate-free result. In this work we conduct adjustments, extensions and simplifications to the algorithm when applying it to a Middle- European urban environment. Based on research conducted in Aalen (Germany), we demonstrate our process of applying TURN for TIR-image normalization at high geometric resolutions and a scene composed of multiple adjacent flight-lines. Additionally, radiometric corrections to the TIR-image were applied prior to its processing by the algorithm. The corrections allow a validation of the TURN results by comparing them to ground-based reference data acquired during the flight with convincing agreement.Attribution 4.0 International LicenseCategories and Subject Descriptors (according to ACM CCS): [100]Computing methodologies Modeling methodologies, [100]Applied computing Environmental sciences[100]Computing methodologies Modeling methodologies[100]Applied computing Environmental sciences10.2312/envirvis.202411358 pages