Environment settings are additional parameters that affect the results of a tool and how the tool is run. The environment settings are available in the Environment settings parameter group in the tool pane.
Output coordinate system
Output coordinate systemspecifies the coordinate system for analysis and the result layer. The following options are available:
- Same as input (default)—The result of your analysis will be in the same coordinate system as the input.
- Choose coordinate system—The result of your analysis will be in the coordinate system you choose. Click the Browse coordinate systems button to choose from a list of coordinate systems.
- Same as layer—The result of your analysis will be in the same coordinate system as an existing layer on the web map. Click the Layer button to choose from a list of layers.
If Same as layer is specified and the chosen layer has a coordinate system defined by a Well-Known Text (WKT) string, the coordinate system will not populate in the parameter and it will not be used in analysis.
Processing extent specifies the extent or boundary when the analysis tool is run. All input features or cells that are completely within or that intersect the specified extent are used in the analysis. The following options are available:
- Full extent (default)—The extent provided by the tool.
- Coordinates—The extent is defined by the coordinates you provide to create a bounding rectangle. Click the Set coordinates from current display extent button to populate the coordinates based on the current map extent.
- Display extent—The extent is defined by the visible extent of the web map at the time when the Run button is clicked.
- Layer—The extent is defined by the spatial extent of an existing layer on the web map. Click the Layer button to choose from a list of layers.
Snap raster adjusts the extent of the output raster layer so it matches the cell alignment of the specified Snap raster layer for raster analysis tools. Click the Layer button to choose from a list of layers.
Cell size specifies the cell size or resolution that is used to create the output raster layer in raster analysis. The following options are available:
- Maximum of inputs (default)—The cell size is defined by the largest cell size of all input layers.
- Minimum of inputs—The cell size is defined by the smallest cell size of all input layers.
- As specified—The cell size is defined using a custom number value.
- From layer—The cell size is defined by the cell size of an existing layer on the web map. Click the Layer button to choose from a list of layers.
Mask specifies a raster layer or feature layer that is used to define your area of interest for raster analysis tools. Only those cells that fall within the analysis mask are considered in the analysis operation. Click the Layer button to choose from a list of layers.
If the analysis mask is a raster, all cells that have a value will define the mask. Cells in a mask raster that are NoData are considered to be outside the mask and will be NoData in the analysis result layer.
If the analysis mask is a feature layer, it will be internally converted to a raster when the tool is run. For this reason, ensure that Cell size and Snap raster are set appropriately for your analysis.
Resampling method specifies how to interpolate pixel values when transforming your raster dataset. This environment is used for raster tools when the input and output do not line up, when the pixel size changes, when the data is shifted, or a combination of these situations. The following options are available:
- Nearest neighbor—Used primarily for discrete data, such as a land-use classification, since it does not create new pixel values. This method is also appropriate for continuous data when you want to preserve the original reflectance values in imagery for accurate multispectral analysis. It is the most efficient in terms of processing time but may introduce small positional errors in the output image. The output image may be offset by up to half a pixel, which may cause the image to have discontinuities and a jagged appearance.
- Bilinear interpolation—This method is most appropriate for continuous data. It performs a bilinear interpolation and determines the new value of a cell based on a weighted distance average of the four nearest input cell centers. It creates an output image that is smoother in appearance than Nearest neighborhood but alters the reflectance values, which results in blurring or loss of image resolution.
- Cubic convolution—Suitable for continuous data. This method performs a cubic convolution and determines the new value of a cell based on fitting a smooth curve through the 16 nearest input cell centers. The result is geometrically less distorted than the raster achieved with Nearest neighbor and sharper than Bilinear interpolation. In some cases, it can result in output pixel values outside the range of input cell values. If this is unacceptable, use the Bilinear interpolation method instead. Cubic convolution is computationally intensive and takes longer to process.