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Ocean_SST_Conceptual

Difference between version 20 and version 19:

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- ## __Percentage Spatial sampling:__ Percentage of the area defined by the min/max latitudes and longitudes to sample. This is determined by the number of samples per field times the number of pixels per sample divided by the total number of pixels in the defined subregion. Spatial sampling is performed on individual 2-d fields. Figure 2 shows the selection of a temporal sample that is to be sampled spatially. Figure 3 shows the randomly selected spatial samples with the area covered by each. [{Image src='ImageStackRandomlySelectedOne.png' caption='Figure 2. Selection of a temporal sample.' height=400 width=400}] [{Image src='RandomSpatialSamples.png' caption='Figure 3. Spatial samples in this temporal sample.' height=400 width=400}]
+ ## __Percentage Spatial sampling:__ Percentage of the area defined by the min/max latitudes and longitudes to sample. To better understand this, we define ''tile''. A tile is a rectangular region that includes a set of pixels. A ''pixel'' is an atomic area and is characterized by an SST value at a lat,long that represents the center of a pixel. The percentage of the area sampled is determined by the number of tiles per field times the number of pixels per tile divided by the total number of pixels in the defined subregion. Spatial sampling is performed on individual 2-d fields. Figure 2 shows the selection of a temporal sample that is to be sampled spatially. Figure 3 shows the randomly selected spatial samples, tiles, with the area covered by each. [{Image src='ImageStackRandomlySelectedOne.png' caption='Figure 2. Selection of a temporal sample.' height=400 width=400}] [{Image src='RandomSpatialSamples.png' caption='Figure 3. Spatial samples in this temporal sample.' height=400 width=400}]
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- ## __TileAveraging:__ A ''tile'' is a rectangular region that includes a set of pixels. A ''pixel'' is atomic an area and characterized by an SST value at a lat,long that represents the center of a pixel.
+ ## __TileAveraging:__ The tiles from different datasets will consist of different numbers of pixels determined by the relative resolution of each data set. Comparing the tile values requires some form of averaging. This parameter defines how the averaging is to be done. For now let's fix this at a straight linear average.

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