Scene normalisation is a process which attempts to remove some of the variance seen in EO data to create values that are independent of view angle or atmospheric state or observing time etc. to give a uniform measure of a given variable across an image. It can be considered as a method to give what would have been observed by the same instrument under viewing identical conditions.
FIDUCEO Vocabulary
Sustained Coordinated Processing of Environmental Satellite Data for Climate Monitoring
Some Level 1 correction schemes involve determining corrections to already calibrated radiances based on some defined reference. These sensor bias corrections can then be applied to correct for gross errors in the original calibration. One example of this are the corrections provided by the GSICS (Global Space-based Inter-Calibration System) consortium for a number of sensors. Note that the terms “Harmonisation” and “Homogenisation” can be applied to this form of correction.
Spinning Enhanced Visible Infra-Red Imager
International sytem of units
SI-Traceability is traceability where the “stated metrological reference” is formally calibrated within the International System of Units (SI) through a National Metrology Institute that participates in the Mutual Recognition Arrangement and whose measurement for this parameter is thus audited through formal international comparison and peer review.
Sea and Land Surface Temperature Radiometer
Simultaneous Nadir Overpass – a location on the planet where the nadir tracks of two satellites intersect within a given spatial and time distance. Both distance measures can vary, depending on the context. This is a special case of a match up as defined above.
Spectral Response Function
SEVIRI Solar Channel Calibration
Special Sensor Microwave/Temperature-2
Sea Surface Temperature
Standard uncertainty describes the standard deviation of the probability distribution describing the spread of possible values.
Means that across many observations there is a deterministic pattern of errors whose amplitude is stochastically drawn from an underlying probability distribution; “structured random” therefore implies “unpredictable” and “correlated across measurements”; the degree of “averaging out” across many measured values depends on the structure of the effect across those measured values; structured 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 structured random; an example of a structured random effect is the impact of a random error in the measurement of signal while viewing a calibration target, which causes unpredictable but inter-related errors in all measured values which use that calibration cycle.
This term refers to the data that a satellite collects by scanning the area below its current location, i.e., the swath or the width of this area perpendicular to the satellite’s flight direction.
Means that the error in a measured value is determined by dependence on some factors; systematic error could in principle be corrected for if the dependencies were understood and the factors were known; where the factors vary negligibly across many measurements, the errors from the systematic effect are the same; “systematic” implies “predictable” (in principle, not in practice) and “correlated across measurements”; systematic errors therefore “average out” slowly or not at all across many measured values; systematic effects may be operating at the same time as other types of effect, in which case only a component of the total error is systematic; an example of a systematic effect is a mis-characterised calibration target.
Effects for a particular measurement process that do not vary (or vary coherently) from (one set of) measurement(s) to (another set of) measurement(s) and therefore produce systematic errors that cannot be reduced by averaging.