Dirk Nuyts

Wildfire detection and characterization from space critically depend on accurate thermal infrared measurements across a wide dynamic range. OroraTech’s SAFIRE payloads feature mid-wave infrared (MWIR) and long-wave infrared (LWIR) bands optimized for this purpose, yet the volume and power constraints of many CubeSat platforms preclude the use of onboard calibration sources. This reflects a broader limitation of current Earth observation systems: the absence of robust calibration and validation methodologies at high brightness temperatures relevant to active fires. We evaluate the potential of using thermophysical models (TPM) of the Moon as a vicarious calibration reference for calibration transfer between instruments. The Moon reaches surface temperatures of up to 400 K, offering a stable target in the thermal domain that is visible from many different orbits. Previous research has established the use of TPMs for Moon observations in the infrared; however, uncertainties in surface properties remain, particularly in the mid-wave infrared. We investigate these effects using SAFIRE observations of the lunar surface acquired over a wide range of lunar phase angles (from waxing -81.5° to waning +122.2°). We constrain the TPMs using observations from the Sentinel-3 Sea and Land Surface Temperature Radiometer (SLSTR) fire channels and uncover a 5.2 % inter-sensor disagreement in the MWIR between Sentinel-3A and Sentinel-3B at high brightness temperatures, corresponding to ~2.2 K at 400 K. Applying the same methodology to observations of our SAFIRE payloads bounds the calibration transfer error at 5.8 % in the MWIR and 4.2 % in the LWIR for lunar phase angles within ±45°. These results establish lunar vicarious calibration as a viable approach in the thermal domain for high-temperature applications, providing a pathway toward improved fire radiative power retrievals and enhanced global wildfire monitoring.

Oil spills in ports are particular cases of oil pollution in water environments that call for specific monitoring measures. Apart from the ecological threats that they pose, their proximity to human activities and the financial losses induced by disturbed port activities add to the need for immediate action. However, in ports, established methods based on short-wave infrared sensors might not be applicable due to the relatively low thickness of the oil layer, and satellite images suffer from insufficient spatial resolution, given the agglomeration of objects in ports. In this study, a lightweight ultraviolet (UV) camera was exploited in both controlled experiments and a real port environment to estimate the potential and limitations of UV imagery in detecting oil spills, in comparison to RGB images. Specifically, motivated by the scarce research literature on this topic, we set up experiments simulating oil spills with various oil types, different viewing angles, and under different weather conditions, such that the separability between oil and background (water) could be better understood and objectively assessed. The UV camera was also used to detect real-world oil spills in a port environment after installing it on a vessel for continuous monitoring. Various separability metrics between water and oil, computed in both scenarios (controlled experiments and port environment), show that the UV cameras have better potential than RGB in detecting oil spills in port environments.