Means that the error in a measured value is considered to be a stochastic independent draw from an underlying probability distribution; “random” implies in this context both “unpredictable” and “uncorrelated across measurements”; random errors therefore tend to “average out” across many measured values; random effects may be operating at the same time as other types of effect, in which case only a component of the total error is random; an example of a random effect (an effect giving rise to random errors) is electronic noise in an amplifier circuit.
FIDUCEO Vocabulary
Random effects are those causing errors that cannot be corrected for in a single measured value, even in principle, because the effect is stochastic. Random effects for a particular measurement process vary unpredictably from (one set of) measurement(s) to (another set of) measurement(s). These produce random errors which are entirely uncorrelated between measurements (or sets of measurements) and generally are reduced by averaging.
This term refers to the process of transforming the information represented in one grid into another grid.
This term refers to the process of transforming the information represented in one type of projection into another type of projection.
A recalibrated dataset is one where the calibration coefficients and/or the calibration algorithm has been updated relative to the operational calibration used to create the original satellite Level 1 datasets. The operational calibration is normally derived from pre-launch measurements and there are many instances where the pre-launch data/algorithm is insufficient to calibrate the sensor in orbit either due to changes in the satellite response while in orbit or due to problems with the pre-launch data/algorithm itself or both.
An uncertainty given in relative units (per cent, parts per million, fractions, etc). This is generally written u(xi)/xi