Impact of Urban Surface Heterogeneity on Land Surface Temperature Correction

Unmanned aerial vehicles (UAVs) enable micro-scale thermal mapping in urban environments, yet thermal imagery records brightness temperature (BT) that is biased by land-surface emissivity () and atmospheric effects.This study develops a single-channel (SC) land surface temperature (LST) retrieval framework that integrates UAV-based thermal and multispectral imagery (MicaSense Altum-PT) with insitu observations.Pixel-wise was estimated using the empirical normalized difference vegetation index (NDVI)- relationship developed for the ASTER spectral response function (SRF), applied to NDVI derived from the Altum-PT RED (668 nm) and near-infrared (842 nm) bands.Background temperature (Tbkg), corresponding to the reflected apparent temperature, was measured using a crumpled aluminum foil temporarily placed within the imaging footprint, which served as a near-perfect reflector to capture ambient longwave radiation, while air temperature (Ta) from on-site loggers; atmospheric transmittance () is fixed under clear-sky conditions.The workflow is demonstrated over the Namdong Industrial Complex (Incheon, Republic of Korea) at 11:00, 13:00, and 15:00 (UTC+9).We quantify the correction magnitude as T=BT-LST within a LiDAR-derived walkable-surface mask and further stratify the results by land cover (Natural vs. Artificial pavements).T is predominantly negative (median: -1.85, -0.95, -0.73 K), indicating systematic BT underestimation relative to LST.Artificial pavements exhibit larger negative T and greater variability than natural cover, reflecting material-dependent emissivity and surfacecondition heterogeneity.The magnitude of |T| generally decreases from morning to afternoon.The results support the use of SC-retrieved LST rather than raw BT for threshold-based assessments (e.g., heatrisk mapping) in pedestrian contexts.Although validated on a single date and site without absolute blackbody references, the framework shows consistent behavior across times and land-cover types, highlighting its utility for urban micro-climate applications.