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Each of these maps was derived using medium to coarse resolution satellite imagery.
Uncertainty in the biomass density maps was derived from a secondary simulation in which the input datasets were resampled to generate 100 replicate training datasets, or realizations, that had the same qualities of the original training dataset, but different random error.
The grouping of regions by claim rate represented in the maps was derived using a software algorithm that computes the natural breaks in the distribution of the variable.
Contrast within the phase maps was derived from pixel-to-pixel variation in the center-of-mass of the carbohydrate absorption band, defined between 4,960 and 4,480 cm−1, using a two-point baseline correction: 4,480 cm−1 and the extreme between 5,100 and 4,900 cm−1.
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Topographical base maps were derived from Ordnance Survey maps of the most similar scale.
Most of the raster maps are derived from vector-based maps first.
Change detection maps are derived in a post-classification change detection.
Statistical parametric maps were derived with pre-specified contrasts, comparing rCBF (Regional Cerebral Blood Fow) during states of interest.
As application, invariant approximation results for this class of maps are derived.
Based on this model, stability maps are derived which can be applied to any kind of fluids and operating conditions.
Biomass maps were derived using empirical models trained with in-situ above ground biomass data per seagrass species.
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Justyna Jupowicz-Kozak
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