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In a paper by the University of Pennsylvania [73], a timing calibration technique is presented that eliminates the need for a specialized data acquisition and can even enable retroactive calibration of datasets where the calibration is missing.
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For the calibration of this dataset, a custom-built metal plate with a size of 140 mm×60 mm×0.5 mm was employed.
For cross-validation purposes, we also performed optimization on dataset #3 and calibration on dataset #2.
We concluded that ALS data can be used as a potential source of data to "enlarge" small ground sample plots and to be used for evaluation and calibration of remotely sensed datasets provided by global systems with coarse spatial resolutions.
Therefore, we can conclude that ALS can be used as a potential source of data to "enlarge" small ground sample plots that can be used for evaluation and calibration of remotely sensed datasets provided by global systems with coarse spatial resolutions.
Finally, based on our findings, we can conclude that ALS data can be used as a potential source of data to "enlarge" small ground sample plots that could be used for evaluation and calibration of remotely sensed datasets provided by global systems with coarse spatial resolutions.
Without an absolute standard, a rigorous relative calibration of the two datasets therefore seems very difficult, if not impossible.
Furthermore, an independent and simple calibration of each satellite dataset was designed to reduce the budget residual.
A 3-step procedure was performed with (1) selection of features, (2) extracting 5 severity classes out of a 3 severity class as defined per expert-opinion and (3) establishment of calibration datasets.
Thus we repeated the calibrations with 10 calibration datasets to obtain robust results.
A slightly more sophisticated category of multivariate analysis is supervised methods, whereby a calibration dataset of known identity is required to build a classification model.
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