Lava flows are one of the main hazards related to effusive basaltic volcanism. To minimize their impact during emplacement, we use lava flow potential distance-to-run predicted by propagation models. These models are partly based on infrared (IR) measurements of lava radiative heat fluxes by remote sensing (RS) methods (ground-based or satellite-based detectors) [1]. These results are however subjected to important errors related to the poor knowledge of spectral emissivity (ε), commonly considered constant by these well-established techniques[2, 3]. This oversimplification is an important source of uncertainties in derived temperatures, which restrain our capacity to accurately model active lava flows. In this study, we developed new algorithms that take into account the effect of spectral emissivity for calculating radiative heat fluxes. We describe the temperature-emissivity relationship with equations established at two wavelengths of interest for RS (10.9 μm and 1.6 μm) that are retrieved from in situ measurements of spectral emissivity for basaltic magma from the 2014–2015 Holuhraun eruption. Spectral emissivity data were systematically acquired over a wide spectral range (400–8000 cm−1) covering TIR, MIR and SWIR, and up to 1473 K [4]. Our results show that spectral emissivity varies linearly with temperature in TIR (10.9 μm), and nonlinearly in SWIR (1.6 μm). We confronted our lab-based results to the field IR data retrieved by [5] and found that temperature precision increases compared to data using constant emissivity value. These new insights will ultimately improve the thermo-rheological models of lava flows [6] in order to support hazard assessment in volcanic systems. References: [1] Kolzenburg et al. 2017. Bull. Volc. 79:45. [2] Harris, A. 2013: Cambridge University press. 728. [3] Rogic et al. 2019 Remote Sens., 11, 662 [4] De Sousa Meneses et al. 2015. Infrared Physics & Technology 69. [5] Aufaristama et al. 2018, Remote Sens, 10,151. [6] Thompson and Ramsey, 2021, Bulletin of Volcanology, 83:41. Keywords: Spectral emissivity, temperature, IR spectroscopy, remote sensing, basalt