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| - !! Conceptual Description of REAP SST Usecase |
| + !! Conceptual Description of REAP SST Usecase |
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| - The goal of the REAP SST usecase workflow (REAP-SST-UCW) is to compare and match-up existing remote-sensed (satellite) images of sea surface temperature found in OPeNDAP archives. |
| + The goal of the REAP SST usecase workflow (REAP-SST-UCW) is to compare and match-up existing remote-sensed (satellite) images of sea surface temperature found in OPeNDAP archives. |
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| - ## __Time sampling:__ Percentage of the dataset times within the timespan. This parameter defines the fraction of temporal fields in the selected subset of the dataset to be sampled. Sampling will be random based on this fraction. Figure 1 is a schematic of a data set, with each gray field corresponding to a latitude, longitude array at one instant in time. The blue slices correspond to fields randomly sampled from the time series. In this case the temporal sampling parameter was approximately 20%. [{Image src='ImageStackRandomlySelected.png' caption='Figure 1. Temporal samples from a time series of SST fields.' height=400 width=400}] |
| - ## __Time span delta:__ Maximum amount of time between a reference dataset time sample and the corresponding sample of another dataset (see Step 2.4) %%(color:red)Not sure what you are referring to here?%% |
| + ## __Time sampling:__ Percentage of the dataset times within the timespan. This parameter defines the fraction of temporal fields in the selected subset of the dataset to be sampled. Sampling will be random based on this fraction. Figure 1 is a schematic of a data set, with each gray field corresponding to a latitude, longitude array at one instant in time. The blue slices correspond to fields randomly sampled from the time series. In this case the temporal sampling parameter was approximately 20%. [{Image src='ImageStackRandomlySelected.png' caption='Figure 1. Temporal samples from a time series of SST fields.' height=400 width=400}] |
| + ## __Time span delta:__ Maximum amount of time between a reference dataset time sample and the corresponding sample of another dataset (see Step 2.4) %%(color:red)Not sure what you are referring to here?%% |
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| - ## __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 samples. [{Image src='ImageStackRandomlySelected.png' caption='Figure 2. Selection of a temporal sample.' height=400 width=400}] [{Image src='ImageStackRandomlySelected.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. 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}] |
| + ## __MinNumberOfPixels:__ This parameter is the minimum number of pixels in each spatial sample. For example if the minimum number of pixels is 9, the sampled area will consist of 3x3 pixels centered on the randomly selected spatial location. In the comparison of several data sets, the number of pixels per sample varies from dataset to dataset. The minimum number in the coarsest dataset defines the spatial region of each sample. This region is then used in the other data sets to define the number of pixels to sample sample from them. The percentage of area sampled in each data set will be approximately the same, although the number of pixels will differ. |
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| - ## __MinNumberOfPixels:__ |
| - ## __Sampling ?__ |
| - ## __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. |
| + ## __Sampling __ This defines the method to use when matching sample locations from one data set to another. We should start with 'Nearest Neighbor' and 'Bi-linear Interpolation'. %%(color:red)We might just start with Nearest Neighbor'. Can add more later.%% |
| + ## __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. |
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| - # __Analyze Match-Up Datasets:__\\ The selected and saved (in an RDBMS) SST match-up dataset values can then be used in statistical comparisons. %%(color: red) To be defined in detail after the implementation of the first two steps. %% |
| + # __Analyze Match-Up Datasets:__\\ The selected and saved (in an RDBMS) SST match-up dataset values can then be used in statistical comparisons. %%(color: red) To be defined in detail after the implementation of the first two steps. %% |
