The Predict Using Trend Raster tool computes a forecasted multidimensional imagery layer using the output trend imagery layer created by the Generate Trend Raster tool.
The output is a hosted imagery layer.
Examples
Example uses of this tool include the following:
- Predict the sea surface temperature in the north Atlantic Ocean for the year 2040 based on sea surface trend information from several prior years.
- Predict the growing degree days for the year 2100 using a trend raster containing trend information for maximum and minimum daily temperature values. Use the Predict Using Trend Raster tool to compute a multidimensional imagery layer containing the daily minimum and maximum temperature values, which can be categorized and counted.
Usage notes
Predict Using Trend Raster includes configurations for the input layer, prediction settings, and the result layer.
Input layer
The Input layer group includes the following parameters:
- Trend imagery layer is the input multidimensional trend raster generated from the Generate Trend Raster tool.
- Variables are the variables of the multidimensional trend imagery layer that will be used for the prediction.
Prediction settings
The Prediction settings group includes the following parameters:
- Dimension definition specifies how the statistic will be extracted from all the dimensions. The options are as follows:
- By value indicates the prediction will be calculated for a single dimension value or a list of dimension values defined by the Values parameter (dimension_values in Python). This is the default. For example, use this option to predict yearly precipitation for the years 2050, 2100, and 2150.
- By interval indicates the prediction will be calculated for an interval of the dimension defined by a start value and an end value. For example, use this option to predict yearly precipitation for every year between 2050 and 2150.
Values specifies the dimension value or values to be used in the prediction when By value is chosen for Dimension definition.
The format of the time, depth, and height values must match the format of the dimension values used to generate the trend raster. If the trend raster was generated for the StdTime dimension, the format would be YYYY-MM-DDTHH:MM:SS, for example 2050-01-01T00:00:00. Multiple values are separated with a semicolon.- Start is the start date, height, or depth of the dimension interval to be used in the prediction when By interval is chosen for Dimension definition.
- End is the end date, height, or depth of the dimension interval to be used in the prediction when By interval is chosen for Dimension definition.
- Interval value is the size of the interval that will be used for the aggregation. This parameter is available when Interval value is chosen for Dimension definition.
- Interval unit specifies the unit that will be used for the interval value. This parameter is available when the Dimension value is a time field and Interval value is chosen for Dimension definition. The options are as follows:
- Hours—The prediction will be calculated for each hour in the range of time described by the Start, End, and Interval value parameters.
- Days—The prediction will be calculated for each day in the range of time described by the Start, End, and Interval value parameters.
- Weeks—The prediction will be calculated for each week in the range of time described by the Start, End, and Interval value parameters.
- Months—The prediction will be calculated for each month in the range of time described by the Start, End, and Interval value parameters.
- Years—The prediction will be calculated for each year in the range of time described by the Start, End, and Interval value parameters.
Result layer
The Result layer group includes the following parameters:
- Output name specifies the name of the layer that is created and added to the map. The name must be unique. If a layer with the same name already exists in your organization, the tool will fail and you will be prompted to use a different name.
- Output layer type specifies the type of raster output that will be created. The output can be either a tiled imagery layer or a dynamic imagery layer.
- Save in folder specifies the name of a folder in My content where the result will be saved.
Environments
Analysis environment settings are additional parameters that affect a tool's results. You can access the tool's analysis environment settings from the Environment settings parameter group.
This tool honors the following analysis environments:
- Output coordinate system
- Processing extent
Note:
The default processing extent in Map Viewer is Full extent. This default is different from Map Viewer Classic in which Use current map extent is enabled by default.
- Snap raster
- Cell size
- Resampling method
Credits
This tool consumes credits.
Use Estimate credits to calculate the number of credits that will be required to run the tool. For more information, see Understand credits for spatial analysis.
Outputs
The output includes one multidimensional imagery layer with the predicted values for the described variable for the specified time period.
Usage requirements
This tool requires the following user type and configurations:
- Professional or Professional Plus user type
- Publisher, Facilitator, or Administrator role, or an equivalent custom role with the Imagery Analysis privilege
Resources
Use the following resources to learn more:
- Predict Using Trend Raster in ArcGIS REST API
- predict_using_trend function in ArcGIS API for Python
- Predict Using Trend Raster in ArcGIS Pro