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Raster functions are operations that process imagery and raster datasets by applying the processing directly to the pixels. Imagine you have imagery of the entire world and you want to calculate the Normalized Difference Vegetation Index (NDVI), which uses the following equation:
(Near Infrared – Red) / (Near Infrared + Red)
The traditional approach is to take the red and near infrared bands, perform this calculation, and write that into a new raster that shows NDVI. Remember, this is global imagery. If you’re only interested in a specific location, why create a raster for the entire globe? What a raster function does is apply that calculation to the pixel on the original data as it is drawn so it is only processing the pixels that are visible on your screen. As you zoom and pan around, the calculations are performed on the fly and no intermediate datasets are created. Why stop at NDVI? You can use functions to create many different information layers which all use the same underlying dataset.
ArcGIS comes with over over 100 out of the box functions that can be used for radiometric and geometric correction, data management, visualization, and analysis. Functions can be applied individually or combined to create function chains. There are several methods for applying functions depending on the structure of the dataset.
There are several methods for applying functions depending on the structure of the dataset.
| Type of dataset | Application method |
|---|---|
| Raster dataset or raster product | Use the f(x) button in the Image Analysis Window. |
| Mosaic dataset | Use the property windows. |
| Image Service | Directly publish functions with the image service or allow the end user to apply them. |
One of the main reasons this repository was created was to have a community where users can learn how to create custom functions and share their work. We’ve decided to use Python as the language for creating custom functions because of its familiarity to the ArcGIS user community. There are advantages to using custom functions. Obviously, if the function you need doesn’t come with ArcGIS, you can create a custom function using Python. We hope to grow the image processing and analytical capability of ArcGIS through this repository by enabling the user community to contribute. Beyond increasing functionality there are other practical needs for using custom functions. For example, if you need to point to specific rasters within a mosaic dataset or call different variables as part of your analysis, that is going to be straight forward using Python. Aggregating rasters is as well. Creating parameters for end users to manipulate is also easier with Python than asking them to break open a function chain (*.rft.xml). Finally, if you have a function chain that relies on many different functions, you can use Python to create an elegant workflow.
Python raster functions will not work with ArcPy. You cannot add them to a geoprocessing model because functions process on the fly and models do not. Custom functions must use the structure laid out in the Anatomy of a Python Raster Function.
Python raster functions are inserted into function chains just like any other function. It accepts one of two inputs; a .py file or a .pyd (complied Cython) file. The parameters for the function are controlled within the Python script, therefore end users can simply point to a script and the function dialog will be populated.
Insert custom functions into a function chain by right clicking on an existing function or raster in the function dialog. The Python Raster Function dialog has three components; the input Python module, the class name and the input parameters.
The input Python module parameter will accept a Python script (.py) or a Cython file (.pyd). After pointing to a Python file the rest of the dialog will be populated.
Choose a Class
The class name parameter will contain the name of the class being used from the python script. In most cases a Python script will contain one class although it is possible to have multiple classes in one Python script. For example, within one script you could compute a number of different vegetation indices, such as NDVI, EVI, SAVI, TSAVI, etc. Each index would be its own class. To select a class, type in the Class Name. By default the first class in the script will be used.
Set Parameters
The parameters are defined in the Python script and you can change the values of each parameter here. For example, a function may have default values that are associated with a specific sensor, such as Landsat 8. If you wanted to apply these functions to Landsat 7, you would have to change the red and near infrared bands because Landsat 8 has a blue band that wasn’t available on earlier sensors. There are 5 possible data types that can be used as parameters; numeric, string, raster, rasters and boolean. Domains can be created for parameters in order to limit the list of input values that a user can chose from. In this case when clicking on the value a drop down menu will appear. For more information on the method that controls input parameters go to the .getParameterInfo() section of the help document.
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Add raster from disk: Add a raster that is on disk. You can add raster datasets, mosaic datasets, and raster products. -
Add function chain: Add a function chain as an input. -
Add scalar: Add a scalar value. Scalar values must be numeric. -
Add reference to selected input: Add a referenced copy of the selected raster or the selected function chain input. A change in the referenced raster or the function chain will be reflected in this referenced copy. This can be useful when creating many Local functions that may use the same referenced input. -
Add copy of selected input: Add a static copy of the selected function chain input. A change in the copied function chain will not reflect this static copy. This can be useful when creating many similar Local functions where there is a slight change in the function chains.