In an earth observation context, we see RAW data as the individual, digitized pixels within an image, where a pixel is the smallest data unit produced by an optical payload’s sensor. In its purest form, Earth Observation data is a measurement of a reflected or transmitted signal. For a passive optical payload, reflected light from the earth’s surface is detected and transformed into a digital stream, and during a calibration process, a unit is assigned to the pixel value.
Earth Observation analysts frequently classify data in terms of spatial, spectral, radiometric, and temporal resolution. These parameters are crucial in determining the data’s information content to detect a specific target. In this case, detection means that the optical payload can “see” the target or object at a specific resolution, contrast, and spectral content.
The real value of CubeSat imager data is unlocked during the data correction and calibration process. However, incorrect geolocation, spectral band misalignment, and pixel intensity variations drastically impact the performance of the Earth Observation data. Therefore, during the calibration process, geometric and radiometric variations across the image plane and the data set are corrected.
Due to size, weight, and power constraints, a CubeSat imager frequently lacks onboard calibration capabilities. Consequently, vicarious calibration techniques, which use known targets on the earth, are used to calibrate CubeSat imagers and intercalibrate between missions.
Hence, when referring to Earth Observation data, it is essential to mention the calibration level. Without a proper calibration step, it becomes challenging to transform the data into information and compare various data sets.