OpenSkyLab | Drone Remote Sensing

Recent advances in drone-based remote sensing have made high-resolution thermal and multispectral data more accessible than ever before. Sensor platforms and flight operations have become relatively user-friendly; however, the radiometric and physical foundations of the data remain widely underappreciated. Raw optical and thermal signals captured by drones are not directly comparable across time, sensors, or environmental conditions without appropriate corrections. Surface reflectance is influenced by illumination geometry, atmospheric scattering and absorption, while thermal measurements depend critically on surface emissivity, humidity, and atmospheric composition. Despite these complexities, many drone users still rely on uncalibrated data products, risking significant bias and misinterpretation. To address this gap, there is a pressing need for targeted education that bridges practical workflows with the underlying principles of radiative transfer, offering a conceptual and methodological foundation for accurate, reproducible environmental monitoring.