Process Raster Collection function

Available with Image Analyst license.

Overview

Processes each slice in a multidimensional raster or each item in a mosaic raster. This function can also aggregate multiple slices into a single slice.

Notes

This function processes each slice in multidimensional raster or mosaic raster using a raster function template. For more information on building a template, see Raster function template. This function supports the following options:

• Specify a raster function template for Item Function. For example, you have a mosaic dataset that contains 20 years of Landsat imagery and you want to calculate the NDVI for each scene in the time series. For Item Function, specify a raster function template that contains the NDVI raster function.

  

• Specify a raster function template for the Aggregation function. For example, you have a multidimensional raster that contains 10 years of daily temperature data and you want to calculate the maximum temperature for each year. In the Aggregation Function pane, specify a raster function template that contains the Cell Statistics function, with operation set to Maximum. Under Aggregation Definition, set Dimension to StdTime, set Type to Interval Keyword, and set Keyword Interval to Yearly.

  Note:

  If the input mosaic dataset is not multidimensional, the aggregation function will not honor the aggregation definition. The aggregation function will aggregate all items or each group into one if they are defined in the aggregation function template. For more information on the use of groups in a mosaic dataset, see Use mosaic dataset items in raster function templates.

  

• Specify a raster function template for Processing Function. The function or function chain in this template is used to display the new processed raster. For example, specify a raster function template that contains the Colormap function to change how the processed raster layer is displayed.

  Note: If the input is a multidimensional raster, the processing function is applied to the current display slice. If the input is a mosaic layer or mosaic dataset, the processing function is applied to the mosaic raster using the First method to resolve overlaps.

  

• Specify templates for any combination of the three functions. For example, you have a mosaic dataset that contains time series Landsat imagery and you want to generate a composite image of maximum NDVI. For Item Function, specify a raster function template that contains the NDVI raster function. For Aggregation Function, specify a raster function template that contains the Cell Statistics function, with operation set to Maximum. For Processing Function, specify a raster function template that contains the Colormap function.

  Note:

  The function processing order follows the order of the input parameters. For example, the Item Function will be processed first.

  

Parameters

Raster Collection	The input multidimensional raster, mosaic layer, or mosaic dataset.
Item Function	Specify the raster function template *.rft.xml used to process each slice or item in the input raster collection.
Aggregation Function	Specify the raster function template *.rft.xml used to aggregate multiple slices into fewer slices or a single slice.
Processing Function	Specify the raster function template *.rft.xml used to display the processed raster layer.
Dimension	The aggregation dimension. This is the dimension or a field along which the variables will be aggregated.
Type	Specifies the dimension interval for which the data will be aggregated. All—The data values will be aggregated across all slices. This is the default. Interval Keyword—The variable data will be aggregated using a commonly known interval. Interval Ranges—The variable data will be aggregated between specified pairs of values or dates. Interval Values—The variable data will be aggregated using a user-specified interval and unit.
Keyword Interval	Specifies the keyword interval that will be used when aggregating along the dimension. This parameter is required when Type is set to Interval Keyword, and the aggregation must be across time. Hourly—The data values will be aggregated into hourly time steps, and the result will include every hour in the time series. Daily—The data values will be aggregated into daily time steps, and the result will include every day in the time series. Weekly—The data values will be aggregated into weekly time steps, and the result will include every week in the time series. Dekadly—The data values will be aggregated into 3 periods of 10 days each. The last period might contain more or fewer than 10 days. The output will include 3 slices for each month. Pentadly—The data values will be aggregated into 6 periods of 5 days each. The last period might contain more or fewer than 5 days. The output will include 6 slices for each month. Monthly—The data values will be aggregated into monthly time steps, and the result will include every month in the time series. Quarterly—The data values will be aggregated into quarterly time steps, and the result will include every quarter in the time series. Yearly—The data values will be aggregated into yearly time steps, and the result will include every year in the time series. Recurring daily—The data values will be aggregated into daily time steps, and the result will include one aggregated value per Julian day. The output will include, at most, 366 daily time slices. Recurring weekly—The data values will be aggregated into weekly time steps, and the result will include one aggregated value per week. The output will include, at most, 53 weekly time slices. Recurring monthly—The data values will be aggregated into monthly time steps, and the result will include one aggregated value per month. The output will include, at most, 12 monthly time slices. Recurring quarterly—The data values will be aggregated into quarterly time steps, and the result will include one aggregated value per quarter. The output will include, at most, 4 quarterly time slices.
Value Interval	The size of the interval that will be used for the aggregation. This parameter is required when the Type parameter is set to Interval Value. For example, to aggregate 30 years of monthly temperature data into 5-year increments, enter 5 for Value Interval, and specify Unit as Years.
Unit	The unit that will be used for the interval value. This parameter is required when Dimension is a time field and the Type parameter is set to Interval Value. If you are aggregating over anything other than time, this option will not be available and the unit for the interval value will match the variable unit of the input multidimensional raster data. Hours—The data values will be aggregated into hourly time slices at the interval provided. Days—The data values will be aggregated into daily time slices at the interval provided. Weeks—The data values will be aggregated into weekly time slices at the interval provided. Months—The data values will be aggregated into monthly time slices at the interval provided. Years—The data values will be aggregated into yearly time slices at the interval provided.
Minimum Value	The minimum value for a range. This parameter is required when the Type parameter is set to Interval Ranges.
Maximum Value	The maximum value for a range. This parameter is required when the Type parameter is set to Interval Ranges.
Where Clause	An expression that filters the records returned. The value is a string that follows SQL expression, such as Cloud Cover < 0.2. See SQL reference for query expressions used in ArcGIS for more information.
Query Geometry	A raster or feature dataset used to filter the images in an area of interest. Only items that intersect with the extent of the dataset will be returned.
Use input features for clipping geometry	When Query Geometry is a feature class, this option filters items that intersect with the geometry.