Use raster functions to customize raster analysis

Distributed raster analytics, based on ArcGIS Image Server, processes raster datasets and remotely sensed imagery with an extensive suite of raster functions. Specified results are automatically stored and published to a distributed raster data store, where they may be shared across your enterprise.

Robust suite of raster analysis functions

Core to this capability is the suite of more than 150 raster functions provided with ArcGIS. These are available as individual processing functions, or they can be combined into a processing chain as raster function templates (RFT). Raster function templates are custom processing chains that can be tailored for any application, using a variety of input data types and processing functions to facilitate specific workflows.

The raster analysis functions can also be extended by the user with the ArcGIS API for Python. Custom raster functions can be written in Python and once they are added to the system they can leverage the distributed processing of raster analysis.

Raster functions and RFT's support important distributed processing and storage paradigms, such as on-premises, cloud and web implementations. Both standard and custom raster processing and storage capabilities are elastic, and can be scaled to account for surges in demand, emergencies, shifting priorities and other effects on required capacity, demand and cost. The raster functions support distributed processing to support dynamic processing environments. As the number of processing instances changes, the distribution of raster analysis processes changes to take advantage of processing and storage resources.

These raster functions and RFT-based workflows can be implemented via ArcGIS Pro, ArcGIS REST API, ArcGIS API for Python, and Java Script API's, as well as Map Viewer in an ArcGIS Enterprise portal. For example, you can use the Generate Raster task to execute distributed raster analysis by giving a JSON object representation of a raster function chain.

Raster functions and objects available for raster analysis

The table below lists the raster functions available for raster analysis in ArcGIS Enterprise Map Viewer. To access the raster functions, open a map, click Analysis which opens the Perform Analysis pane. Click Raster Analysis to open the Raster Analysis pane and display the raster function available in the various catagories, such as Analysis Patterns, Analyze Image, and Multidimensional Analysis.

You can use raster functions and build your own custom raster function template chains in the Raster Function Editor. Click the button at the top of the Raster Analysis pane to open the Raster Function Template window. The available raster functions are listed in the left pane; select your raster function and click Add Function to add it to the Raster Function Editor and build your raster function template. Name your raster function chain and save it.

The raster functions available from the Raster Analysis pane in Map Viewer are listed below.

Analysis

Raster Function	Description	Object API
Binary Thresholding	The binary Threshold function divides your raster into two distinct classes using the Otsu method, which distinguishes between background and foreground in imagery by creating two classes with minimal intraclass variance. For more information, see Binary Thresholding raster function.	Python
CCDC Analysis	Evaluates changes in pixel values over time using the Continuous Change Detection and Classification (CCDC) method and generates a multidimensional raster containing the model results. See the raster function CCDC Analysis raster function.	REST
Compute Change	Computes the differences between to categorical or continuous raster datasets. For more info, see Compute Change raster function.
Detect Change Using Change Analysis	Generates a raster containing pixel change information using the output change analysis raster from the Analyze Changes Using CCDC tool. For more info, see Detect Change Using Change Analysis raster function.	REST
Generate Trend	Estimates the trend for each pixel along a dimension for a given variable in a multidimensional raster. For more info, see the Generate Trend raster function.	Python | REST
Heat index	Calculates apparent temperature based on ambient temperature and relative humidity. For more info, see the Heat Index raster function.
Kernel density	Calculates a magnitude-per-unit area from point or polyline features, using a kernel function to fit a smoothly tapered surface to each point or polyline. For more info, see Kernel Density raster function.	Python
NDVI	The Normalized Difference Vegetation Index (NDVI) is a standardized index that allows you to generate an image displaying greenness (relative biomass). This index takes advantage of the contrast of the characteristics of two bands from a multispectral raster dataset—the chlorophyll pigment absorptions in the red band and the high reflectivity of plant materials in the near-infrared (NIR) band. For more information, see NDVI function.	Python
NDVI Colorized	Applies the NDVI function on the input image, and then uses a color map or color ramp to display the result. For more info, see the NDVI Colorized raster function.
Predict Using Trend	Generates a forecasted layer using the output from the Generate Trend function. For more info, see the Predict Using Trend raster function.	Python | REST
Process Raster Collection	Processes each slice in a multidimensional raster layer or each item in a mosaic layer. For more info, see the Process Raster Collection raster function.	Python
Tasseled Cap	Provides standardized detection of man-made features, soil, and vegetation by measuring levels of brightness, greenness, and wetness. For more information, see the Tasseled Cap raster function.	Python
Weighted overlay	Overlays several rasters using a common measurement scale and weights each according to its importance. The Weighted Overlay function allows you to overlay several rasters using a common measurement scale and weight each according to its importance. For more info, see Weighted Overlay raster function.	Python
Weighted sum	Weights and adds an array of rasters on a cell-by-cell basis. The Weighted Sum function allows you to overlay several rasters, multiplying each by their given weight and summing them together. For more info, see the Weighted Sum raster function.	Python
Wind chill	Wind chill is a way to measure how cold it feels when wind is taken into account. For more info, see the Wind Chill raster function.

Appearance

Raster Function	Description	Object API
Contrast and brightness	Adjusts the differences between colors and overall brightness of the image. For more info, see the Contrast and Brightness raster functions.	Python
Convolution	Filters an image, which can be used to sharpen, blur, and detect edges within an image, or other kernel-based enhancements. For more info see the Convolution raster function.	Python
Pansharpening	Enhances the spatial resolution of a multiband image by fusing it with a higher-resolution panchromatic image. For more info see the Pansharpening raster function.	Python
Statistics and Histogram	Defines the descriptive statistics for a dataset or uses the distribution from another dataset. For more info, see the Statistics and Histogram raster function.	Python
Stretch	Calculates the focal statistics for each pixel of an image, base on a defined focal neighborhood. For more info, see the Stretch raster function.	Python

Classification

Raster Function	Description	Object API
Classify	Applies the appropriate classifier and associated training data specified in the .ecd training file to a raster dataset or segmented raster. For more info, see the Classify raster function.	Pyton | REST
Linear Spectral Unmixing	Performs subpixel classification and calculates the fractional abundance of different land cover types for individual pixels. For more info, see the Linear Spectral Unmixing raster function.	Python | REST
ML Classify	Uses the maximum likelihood algorithm to assign pixels to a class. For more information, see ML Classify raster function.	Python
Region grow	Grows regions from seed points. The Region Grow function categorizes neighboring pixels into groups depending on the specified radius from the seed point. The group of pixels is assigned a specific fill value. For more info, see Region Grow raster function.
Segment Mean Shift	Groups pixels that are adjacent and have similar spectral or spatial characteristics into segments. This can be used as a second raster in the Classify. For more info, see the Segment Mean Shift raster function and Understanding segmentation and classification.	Python | REST

Conversion

Raster Function	Description	Object API
Color model conversion	Converts the color model of an image from either the HSV (hue, saturation, and value) model to RGB (red, green, and blue), or from RGB to HSV. For more info, see Color Model Conversion raster function.	Python
Colormap	Transforms the pixel values to display the raster data as a grayscale or a red, green, blue (RGB) image, based on a color map. For more info, see the Colormap raster function.	Python
Colormap to RGB	Converts a single-band raster with a color map to a three-band RGB (red, green, and blue) raster. For more info, see the Colormap to RGB raster function.	Python
Complex	Derives the magnitude from RADARSAT data so it can be displayed. For more info, see the Complex raster function.	Python
Grayscale	Converts a multiband image into a single-band grayscale image. Specified weights can be applied to each of the input bands. For more info, see the Grayscale raster function.	Python
Rasterize attributes	Enriches a raster by adding bands derived from values of specified attributes from an external table or a feature service. For more info, see Rasterize Attributes raster functions.
Rasterize features	Converts features to raster. Features are assigned pixel values based on the feature's field, such as OBJECTID. Optionally, the pixel values can be based on a user-defined value field in the input feature's attribute table. For more info, see the Rasterize Features raster function.
Spectral conversion	Applies a matrix to a multiband image to convert a false color image to a pseudo color image. For more info, see the Spectral Conversion raster function.	Python
Terrain To Raster	Render multipoint data managed using a terrain dataset stored in a geodatabase. For more info, see the Terrain to Raster function.
Trend to RGB	Converts a trend raster to a three-band (red, green, and blue) raster. The trend raster is generated from the Generate Trend raster function or the CCDC Analysis raster function. For more info, see the Trend to RGB raster function.
Unit conversion	Converts from one unit of measurement to another. For more info, see the Unit Conversion raster function.	Python
Vector field	Composite two single-band rasters (each raster represents U/V or Magnitude/Direction) into a two-band raster (each band represents U/V or Magnitude/Direction). Data combination type (U-V or Magnitude-Direction) can also be converted interchangeably with this function. For more info, see the Vector Field raster function.	Python

Correction

Raster Function	Description	Object API
Apparent reflectance	Calibrates the digital number (DN) values of imagery from some satellite sensors. The calibration uses sun elevation, acquisition date, sensor gain and bias for each band to derive Top of Atmosphere reflectance, plus sun angle correction. For more info, see the Apparent Reflectance raster function.
Geometric	Orthorectifies the image based on a sensor definition and a terrain model. For more info, see the Geometric raster function.	Python
Radar calibration	Calibration is performed on radar imagery so that the pixel values are a true representation of the radar backscatter. For more info, see the Radar Calibration raster function.
Sentinel-1 Radiometric Calibration	Performs different types of radiometric calibration on Sentinel-1 data. For more info, see the Sentinel-1 Radiometric Calibration raster function.	Python
Sentinel-1 Thermal Noise Removal	Removes thermal noise from Sentinel-1 data. For more info, see the Sentinel-1 Thermal Noise Removal raster function.	Python
Speckle	Filters the speckled radar dataset and smooths out the noise while retaining the edges or sharp features in the image. For more info, see the Speckle raster function.	Python

Data Management

Raster Function	Description	Object API
Aggregate	Generates a multidimensional raster dataset by combining existing multidimensional raster variables along a dimension. For more info, see the Aggregate raster function.	Python | REST
Attribute Table	Uses an attribute table to symbolize a single-band raster. This is useful when you want to present imagery with specific labels and colors. If your table contains fields named red, green, and blue, values within those fields will be used like a color map when rendering the image. For more info, see the Attribute Table raster function.
Buffered	Buffers the last accessed pixel blocks. See Buffered raster function for more info.
Cached Raster	The Caches Raster function cerates a preprocessed cache at the point in the function chain preceding the functions that can impede performance due to more computationally intensive processing. These demanding functions can include Convolution, Band Arithmetic, Pansharpen, Geometric as well as multiple Arithmetic functions. For more info, see the Cached Raster function.
Clip	Clips a raster using a rectangular shape according to the extents defined or clips a raster to the shape of an input polygon feature class. The shape defining the clip can clip out the extent of the raster, or clip out an area within the raster. For more info, see the Clip raster function.	Python
Composite Bands	Combines multiple rasters into one multiband raster. For more info see the Composite Bands raster function.	Python
Constant	Creates a virtual raster with a single pixel value that can be used in raster function templates and to process a mosaic dataset. The constant value is used for every pixel value in the raster. For more info see the Constant raster function.	Python
Expand	Expands specified zones of a raster by zones by a specified number of cells. For more info, see the Expand raster function.
Extract Bands	Reorders or extracts bands from a raster. For more info, see the Extract Bands raster function.	Python
Interpolate irregular data	The interpolate irregular data function takes the irregularly gridded data and resamples it so each pixel is of uniform size and is square. For more info, see the Interpolate irregular data raster function.	Python
Key metadata	This function allows you to insert or override key metadata of a raster. For more info, see the Key Metadata raster function.
Mask	Creates NoData by defining a range of pixel values. Any values outside the range return as NoData. For more info, see the Mask raster function.	Python
Mosaic Rasters	Stitches a set of raster datasets together to create one dataset. For more info, see the Mosaic Rasters function.
Multidimensional Filter	Creates a raster layer from a multidimensional raster dataset by slicing data along defined variables and dimensions. For more info, see the Multidimensional Filter raster function.	Python
Multidimensional Raster	Adds a multidimensional dataset as a multidimensional raster layer. For more info, see the Multidimensional Raster function.
Nibble	Replaces selected cells of a raster with the value of their nearest neighbor. This is useful for editing areas of a raster in which the data may be erroneous. For more info, see the Nibble raster function.	Python | REST
Random	Creates a virtual raster with random pixel values that can be used in a mosaic dataset. For ore info, see the Random raster function.	Python
Raster Info	The Raster Info function modifies properties of the raster, such as bit depth, a NoData value, cell size, extent, and so on. For more info, see the Raster Info raster function.
Recast	Dynamically modifies the function parameter used in a mosaic dataset or image service without physically persisting the changes. For more info, see the Recast raster function.
Region Group	Records, for each cell in the output, the identity of the connected region to which that cell belongs. A unique number is assigned to each region. For more info, see the Region Group raster function.	Python
Reproject	Modifies the projection of a raster dataset, mosaic dataset, or raster item in a mosaic dataset. It can also resample the data to a new cell size and define an origin. For more info, see the Reproject raster function.
Resample	Changes the spatial resolution of a dataset. For more info, see the Resample raster function.	Python
Shrink	Shrinks specified zones of a raster by a specified number of cells. For more info, see the Shrink raster function.	Python
Swath	Interpolates from irregular grids or swath data. For more info, see the Swath raster function.
Transpose Bits	Unpacks the bits of the input pixel and maps them to specified bits in the output pixel. The purpose of this function is to manipulate bits from a couple of inputs, such as the Landsat 8 quality band products. For more info, see Transpose Bits raster function.	Python

Distance

Raster Function	Description	Object API
Corridor	Calculates the sum of accumulative costs for two input accumulative cost rasters. For more info, see the Corridor raster function.	Python
Cost Allocation	Calculates, for each cell, its least-cost source based on the least accumulative cost over a cost surface. For more details, see the Cost Allocation raster function.	Python
Cost Back Link	Defines the neighbor that is the next cell on the least-accumulative cost path to the least-cost source. For more info, see the Cost Back Link raster function.	Python
Cost Distance	Calculates the least-accumulative cost distance for each cell from or to the least-cost source over a cost surface. For more info, see Cost Distance raster function.	Python
Cost Path	Calculates the least-cost path from a source to a destination. For more info, see the Cost Path raster function.	Python | REST
Distance Accumulation	Calculates accumulated distance for each cell to sources, allowing for straight-line distance, cost distance, true surface distance, as well as vertical and horizontal cost factors. For more info, see the Distance Accumulation raster function.	Python | REST
Distance Allocation	Calculates distance allocation for each cell to the provided sources based on straight-line distance, cost distance, true surface distance, as well as vertical and horizontal cost factors. For more info, see the Distance Allocation raster function.	Python | REST
Euclidean Allocation	Calculates, for each cell, the nearest source based on Euclidean distance. For more info, see the Euclidean Allocation raster function.	Python
Euclidean Back Direction	Calculates, for each cell, the direction, in degrees, to the neighboring cell along the shortest path back to the closest source while avoiding barriers. For more info, see the Euclidean Back Direction raster function.	Python
Euclidean Direction	Calculates, for each cell, the direction, in degrees, to the nearest source. For more info, see the Euclidean Direction raster function.	Python
Euclidean Distance	Calculates, for each cell, the Euclidean distance to the closest source. For more info, see the Euclidean Distance raster function.	Python
Least cost path	Calculates the least-cost path from a source to a destination. The least accumulative cost distance is calculated for each cell over a cost surface, to the nearest source. This produces an output raster that records the least-cost path, or paths, from selected locations to the closest source cells defined within the accumulative cost surface, in terms of cost distance. For more info, see the Least cost path raster function.	Python
Optimal Path As Raster	Calculates the optimal path from destinations to sources. For more info, see Optimal Path As Raster raster function.	Python
Path Distance	Calculates, for each cell, the least accumulative cost distance from or to the least-cost source, while accounting for surface distance along with horizontal and vertical cost factors. For more info, see Path Distance raster function.	Python
Path Distance Allocation	Calculates the least-cost source for each cell based on the least accumulative cost over a cost surface, while accounting for surface distance along with horizontal and vertical cost factors. For more info, see Path Distance Allocation raster function.	Python
Path Distance Back Link	Defines the neighbor that is the next cell on the least accumulative cost path to the least-cost source, while accounting for surface distance along with horizontal and vertical cost factors. For more info, see Path Distance Back Link raster function.	Python

Hydrology

Raster Function	Description	Object API
Fill	Fills sinks and peaks in an elevation surface raster to remove small imperfections in the data. For more info, see the Fill raster function.	Python | REST
Flow Accumulation	Creates a raster layer of accumulated flow into each cell. A weight factor can optionally be applied. For more info, see the Flow Accumulation raster function.	Python | REST
Flow Direction	Creates a raster layer of flow direction from each cell to its steepest downslope neighbor. For more info, see the Flow Direction raster function.	Python | REST
Flow Distance	Computes the minimum downslope horizontal or vertical distance to cell(s) on a stream or river into which they flow. For more info, see the Flow Distance raster function.	Python | REST
Flow Length	Creates a raster layer of upstream or downstream distance, or weighted distance, along the flow path for each cell. For more info, see the Flow Length raster function.	Python
Sink	Creates a raster layer identifying all sinks or areas of internal drainage. For more info, see the Sink raster function.	Python
Snap Pour Point	Snaps pour points to the cell of highest flow accumulation within a specified distance. For more info, see the Snap Pour Point raster function.	Python
Stream Link	Assigns unique values to sections of a raster linear network between intersections. For more info, see the Stream Link raster function.	Python | REST
Stream Order	Creates a raster layer that assigns a numeric order to segments of a raster representing branches of a linear network. For more info, see the Stream Order raster function.	Python
Watershed	Determines the contributing area above a set of cells in a raster. For more info, see the Watershed raster function.	Python | REST

Math

Raster Function	Description	Object API
Absolute value	Calculates the absolute value of the pixels in a raster.	Python
Arithmetic	Uses the pixel values to calculate mathematical operations on overlapping rasters.	Python
Band arithmetic	Calculates indexes using predefined formulas or a user-defined expression.	Python
Calculator	Computes a raster from a raster based mathematical expression.	Python
Divide	Divides the values of two rasters on a pixel-by-pixel basis.	Python
Exponent	Calculates the base e exponential of the pixels in a raster.	Python
Exp10	Calculates the base 2 exponential of the pixels in a raster.	Python
Exp2	Calculates the base 10 exponential of the pixels in a raster.	Python
Float	Converts each pixel value of a raster into a floating-point representation.	Python
Integer	Converts each pixel value of a raster to an integer by truncation.	Python
Ln	Calculates the natural logarithm (base e) of each pixel in a raster.	Python
Log10	Calculates the base 10 logarithm of each pixel in a raster.	Python
Log2	Calculates the base 2 logarithm of each pixel in a raster.	Python
Minus	Subtracts the value of the second input raster from the value of the first input raster on a pixel-by-pixel basis.	Python
Modulo	Finds the remainder (modulo) of the first raster when divided by the second raster on a pixel-by-pixel basis.	Python
Negate	Changes the sign (multiplies by -1) of the pixel values of the input raster on a pixel-by-pixel basis.	Python
Plus	Adds (sums) the values of two rasters on a pixel-by-pixel basis.	Python
Power	Raises the pixel values in a raster to the power of the values found in another raster.	Python
Round Down	Returns the next lower integer, as a floating-point value, for each pixel in a raster.	Python
Round Up	Returns the next higher integer, as a floating-point value, for each pixel in a raster.	Python
Square	Calculates the square of the pixel values in a raster.	Python
Square root	Calculates the square root of the pixel values in a raster.	Python
Times	Multiplies the values of two rasters on a pixel-by-pixel basis.	Python

Math: Conditional

Raster Function	Description	Object API
Con	Performs a conditional If, Then, Else operation. When a Con operator is used, there usually needs to be two or more functions chained together, where one function states the criteria and the second function is the Con operator which uses the criteria and dictates what the true and false outputs should be.	Python
Set Null	Set Null sets identified cell locations to NoData based on a specified criteria. It returns NoData if a conditional evaluation is true, and returns the value specified by another raster if it is false.	Python

Math: Logical

Raster Function	Description	Object API
Bitwise And	Performs a Bitwise And operation on the binary values of two input rasters. Learn more about how Bitwise math tools work	Python
Bitwise Left Shift	Performs a Bitwise Left Shift operation on the binary values of two input rasters.	Python
Bitwise Not	Performs a Bitwise Not (complement) operation on the binary value of an input raster.	Python
Bitwise Or	Performs a Bitwise Or operation on the binary values of two input rasters.	Python
Bitwise Right Shift	Performs a Bitwise Right Shift operation on the binary values of two input rasters.	Python
Bitwise Xor	Performs a Bitwise eXclusive Or operation on the binary values of two input rasters.	Python
Boolean And	Performs a Boolean And operation on the pixel values of two input rasters. If both input values are true (nonzero), the output value is 1. If one or both input values are false (zero), the output value is 0. Learn more about how the Boolean math tools work	Python
Boolean Not	Performs a Boolean Not (complement) operation on the pixel values of the input raster. If the input values are true (nonzero), the output value is 0. If the input values are false (zero), the output value is 1.	Python
Boolean Or	Performs a Boolean Or operation on the cell values of two input rasters. If one or both input values are true (nonzero), the output value is 1. If both input values are false (zero), the output value is 0.	Python
Boolean Xor	Performs a Boolean eXclusive Or operation on the cell values of two input rasters. If one input value is true (nonzero) and the other value is false (zero), the output value is 1. If both input values are true or both are false, the output value is 0.	Python
Equal To	Performs an equal-to operation on two rasters on a pixel-by-pixel basis.	Python
Greater Than	Performs a Relational greater-than operation on two inputs on a pixel-by-pixel basis. Returns a value of 1 for pixels where the first raster is greater than the second raster and a value of 0 for pixels where the first raster is not greater than the second raster. Learn more about how the Relational math tools work	Python
Greater Than Equal	Performs a Relational greater-than-or-equal-to operation on two inputs on a pixel-by-pixel basis. Returns a value of 1 for pixels where the first raster is greater than or equal to the second raster and a value of 0 for pixels where the first raster is not greater than or equal to the second raster.	Python
Is Null	Determines which values from the input raster are NoData on a pixel-by-pixel basis. Returns a value of 1 if the input value is NoData and a value of 0 for pixels that are not NoData.	Python
Less Than	Performs a Relational less-than operation on two inputs on a pixel-by-pixel basis. Returns a value of 1 for pixels where the first raster is not less than the second raster.	Python
Less Than Equal	Performs a Relational less-than-or-equal-to operation on two inputs on a pixel-by-pixel basis. Returns a value of 1 for pixels where the first raster is less than or equal to the second raster and a value of 0 where it is not less than or equal to the second raster.	Python
Not Equal	Performs a Relational not-equal-to operation on two inputs on a pixel-by-pixel basis. Returns a value of 1 for pixels where the first raster is not equal to the second raster and a value of 0 for pixels where it is equal to the second raster.	Python

Trigonometric

Raster Function	Description	Object API
ACos	Calculates the inverse cosine of the pixels in a raster.	Python
ACosH	Calculates the inverse hyperbolic cosine of the pixels in a raster.	Python
ASin	Calculates the inverse sine of the pixels in a raster.	Python
ASinH	Calculates the inverse hyperbolic sine of the pixels in a raster.	Python
ATan	Calculates the inverse tangent of the pixels in a raster.	Python
ATan2	Calculates the inverse tangent (based on x,y) of the pixels in a raster.	Python
ATanH	Calculates the inverse hyperbolic tangent of the pixels in a raster.	Python
Cos	Calculates the cosine of the pixels in a raster.	Python
CosH	Calculates the hyperbolic cosine of the pixels in a raster.	Python
Sin	Calculates the sine of the pixels in a raster.	Python
SinH	Calculates the hyperbolic sine of the pixels in a raster.	Python
Tan	Calculates the tangent of the pixels in a raster.	Python
TanH	Calculates the hyperbolic tangent of the pixels in a raster.	Python

Math: Reclass

Raster Function	Description	Object API
Lookup	Creates a new raster by looking up values found in another field in the table of the input raster.	Python
Remap	Allows you to group pixel values together and assign the group a new value.	Python
Zonal Remap	Allows you to remap pixels in a raster based on zones defined in another raster and zone-dependent value mapping defined in a table.

Statistical

Raster Function	Description	Object API
ArgStatistics	Orders raster bands into an array and identifies the band that has the minimum, maximum, median, or duration of pixel values.	Python
Cell statistics	Calculates statistics from multiple rasters on a pixel-by-pixel basis. The available statistics are Majority, Maximum, Mean, Median, Minimum, Minority, Range, Standard Deviation, Sum, and Variety.
Focal Statistics	Calculates statistics on the cells within a neighborhood around each cell of an input raster. Several shapes of neighborhood are available.	Python
Statistics	Defines a neighborhood and calculates the statistics within those pixels.	Python
Zonal statistics	Calculates statistics on values of a raster within the zones of another dataset.	Python

Surface

Raster Function	Description	Object API
Aspect	The Aspect function identifies the downslope direction of the maximum rate of change in value from each cell to its neighbors. For more info, see the Aspect raster function.	Python
Aspect-Slope	Creates a raster layer that simultaneously displays the aspect and slope of a surface. For more info, see the Aspect-Slope raster function.
Contour	Generates contour lines by joining points with the same elevation from a raster elevation dataset. The contours are isolines created as rasters for visualization. For more info, see the Contour raster function.
Curvature	Displays the shape or curvature of the slope. A part of a surface can be concave or convex; you can tell that by looking at the curvature value. The curvature is calculated by computing the second derivative of the surface. For more info, see the Curvature raster function.	Python
Elevation void fill	The Elevation Void Fill function is used to create pixels where holes exist in your elevation. For more info, see the Elevation Void Fill raster function.	Python
Hillshade	The hillshade function produces a grayscale 3D representation of the terrain surface, with the sun's relative position taken into account for shading the image. For more info, see the Hillshade raster function.	Python
Shaded relief	The Shaded relief function creates a color 3D representation of the terrain by merging the images from the elevation-coded and hillshade methods. This function uses the altitude and azimuth properties to specify the sun's position. For more info, see the Shaded Relief raster function.	Python
Slope	The Slope function represents the rate of change of elevation for each digital elevation model (DEM) cell. It's the first derivative of a DEM. For more info, see the Slope raster function.	Python
Viewshed	Determines the raster surface locations visible to a set of observer features using geodesic methods. For more info, see the Viewshed raster function.	REST