Raster

Calculates the absolute value of each raster cell.

Reduces raster resolution by aggregating blocks of cells.

Detects temporal changes in raster imagery using the CCDC method.

Evaluates statistical differences between multiple series or layers using ANOVA.

Calculates the arccosine of each cell value in a raster.

Calculates the inverse hyperbolic cosine of each raster cell.

Calculates the arcsine of each cell value in a raster.

Calculates the arctangent of each cell value in a raster.

Calculates the inverse hyperbolic sine of each raster cell.

Calculates the inverse hyperbolic tangent of each raster cell.

Calculates the arctangent angle from two rasters.

Summarizes raster values using band collection statistics.

Calculates the maximum of each block of cells in a raster.

Calculates the minimum of each block of cells in a raster.

Summarizes raster values using block statistics.

Cleans irregular boundaries between raster classes using neighborhood majority operations.

Calculates boundary shape complexity on a raster.

Rounds up each decimal value in the input raster layer.

Summarizes raster values using cell statistics.

Marks the centroid cell of each raster region.

Compares a raster classification against reference data and calculates per-class accuracy measures.

Clips a raster to the exact extent of a mask polygon.

Calculates groupings of contiguous cells on a raster.

Combines categories from multiple rasters into a raster of unique combinations.

Generates contour lines without crossing barriers that interrupt interpolation.

Identifies least-cost accumulated corridors between two distance surfaces.

Calculates the trigonometric cosine of each cell value in the raster.

Calculates the hyperbolic cosine of each raster cell.

Generates a flat raster with defined gradient, orientation, and constant, using a base raster for extent and resolution.

Quantifies the crispness of a probability image to assess separation between fuzzy classes.

Counts value combinations of two categorical rasters in a cross-tabulation table.

Calculates for each cell the cumulative probability of its raster value.

Calculates cut and fill volumes between surfaces over a raster.

Models groundwater flow using Darcy's law.

Clusters dense cells or points with DBSCAN and separates noise features.

Subtracts one unit from each valid cell of the input raster.

Filters a digital elevation model to highlight specific terrain features.

Detects pixels with values unusual relative to their neighborhood or image distribution.

Generates an interpolated surface using diffusion with barriers.

Calculates the proportion of edge cells within a raster neighborhood.

Interpolates a surface incorporating estimated uncertainty and spatial variation via empirical Bayesian kriging.

Compares two rasters and marks cells with equal values.

Assigns NoData to cells covered by input polygons.

Calculates for each cell the direction to the nearest Euclidean source.

Raises the constant e to each cell value of the input raster.

Calculates two raised to each cell value over a raster.

Expands or shrinks categorical zones by a specified cell distance.

Extracts requested extents or bands from a COG and produces a reduced raster for the area of interest.

Downloads a requested extent from a WMS service as a raster for analysis.

Assembles XYZ tiles covering the requested extent into an output raster.

Generates a structured random field using a fast Fourier transform.

Removes raster regions whose area does not meet the specified threshold.

Returns the position of the layer containing the requested statistic for each cell.

Marks cells located on the edge of raster patches or classes.

Rounds down decimal values of each raster cell.

Models local flow movement between cells based on a defined neighborhood.

Summarizes raster values using focal statistics.

Combines rasters through fuzzy overlay and outputs a raster of calculated values.

Generates Gaussian realizations honoring the specified spatial variability model.

Calculates the anomaly of each slice of a multidimensional raster against its temporal reference.

Fits linear, harmonic, or polynomial trends per pixel along a dimension of a multidimensional raster.

Compares two rasters and marks cells where the first is greater.

Compares two rasters and marks cells where the first is greater or equal.

Estimates a density surface using a kernel around features.

Interpolates a 3D surface weighting observations by inverse distance.

Interpolates a surface weighting nearby points by inverse distance.

Measures spatial autocorrelation of values within a raster image.

Computes correlation between values of two coincident raster images.

Fits a regression between bands or images and outputs the estimated raster.

Adds one unit to each raster cell and updates its values.

Adds values to an existing raster cell by cell and updates the same file.

Divides original raster values and saves the result to the same file.

Multiplies an existing raster by another raster or constant and updates the same file.

Subtracts one raster from another and overwrites the target raster file.

Divides two rasters' values keeping only the integer quotient.

Interpolates values from points with spatial and temporal coordinates into a surface.

Interpolates values from points while honoring barriers that block propagation between zones.

Reconstructs raster bands from their inverse principal components.

Flags cells containing NoData to locate gaps in raster coverage.

Evaluates agreement between observed and reference classifications using the kappa index.

Computes kernel density ratio on a raster.

Generates an interpolated surface via kernel interpolation with barriers.

Tests whether value distribution fits a normal distribution using the KS test.

Detects temporal changes in image time series using LandTrendr.

Summarizes height distribution of a LiDAR point cloud with statistical metrics.

Compares two rasters and flags cells where the first is less than the second.

Compares two rasters and flags cells where the first is less than or equal.

Computes line length per unit area, producing a density surface.

Summarizes raster values using line statistics.

Lists distinct values in a raster for class review.

Computes the natural logarithm of each raster cell.

Fits polynomials in local neighborhoods to estimate a surface from points.

Identifies candidate regions by size, value, or suitability criteria and outputs their locations.

Computes the base-10 logarithm of each raster cell.

Computes the base-2 logarithm of each raster cell.

Extracts or assigns cartographic features from a raster based on cell values.

Performs matched filter target detection (CEM/ACE) on a raster.

Returns the maximum value per cell when comparing rasters or a constant.

Classifies raster pixels using maximum likelihood and outputs a class raster.

Returns the minimum value per cell when comparing rasters or a constant.

Interpolates a surface from points using the modified Shepard method.

Combines rasters via multicriteria overlay, outputting a raster of computed values.

Averages SAR image neighborhoods to reduce speckle and stabilize values.

Measures local narrowness of raster shapes to highlight corridors, bottlenecks, or elongated features.

Changes the sign of each raster value and outputs the inverted raster.

Fills selected raster cells with values from their nearest neighbors.

Compares two rasters or a raster and a constant, flagging cells with differing values.

Estimates a surface using optimal interpolation from known points.

Interpolates a variable using an additional spatially correlated secondary variable.

Computes a paired-sample t-test on a raster.

Calculates accumulated distance following travel costs and directions between cells.

Generates contours delimiting specified percentiles of a raster surface.

Measures association between two binary variables using the phi coefficient.

Summarizes raster values using point statistics.

Simulates dispersion of a point-source release accounting for medium porosity.

Generates a predicted multidimensional raster for given time, depth, or height values from a trend raster.

Models probability or suitability from known presence records and predictor variables.

Reduces correlated bands into independent components concentrating spectral variation.

Extracts and displays tags and metadata stored in a GeoTIFF file.

Interpolates values across zones while preserving original totals per area.

Classifies raster values into intervals with equal numbers of cells.

Generates an interpolated surface using radial basis functions.

Calculates the spatial dispersion of each raster region relative to its centroid.

Generates a random field according to specified distribution and autocorrelation parameters.

Fits a random forest classification model on raster data.

Applies a trained random forest model to raster bands and produces a per-pixel classification.

Fits a random forest regression model on raster data.

Applies a random forest model to explanatory rasters and estimates a continuous value per pixel.

Randomly selects a specified number of cells and marks their locations in a new raster.

Calculates the area of each raster class or region from its cells.

Evaluates a mathematical expression across rasters and outputs the resulting raster.

Assigns each cell the identifier of the source that determines its value.

Generates a frequency histogram of the values contained in a raster.

Normalizes raster values to a common scale.

Calculates the perimeter of each region or class identified in a raster.

Summarizes the raster with minimum, maximum, mean, and standard deviation.

Computes the multiplicative inverse of each cell and outputs a reciprocal raster.

Exports a raster rendering as a PNG image for visualization or publication.

Rescales raster values using a user-defined transformation function.

Rescales the range of values in a raster.

Calculates the root mean square error between observed and estimated values.

Rounds each raster cell value to the nearest integer.

Compares the phase of two SAR images to estimate coherence and surface changes.

Measures irregularity or compactness of patches and regions, producing a per-class raster index.

Removes raster regions smaller than a threshold and replaces them with neighboring classes.

Computes the sine of each cell value and creates a transformed raster.

Computes the hyperbolic sine of each raster cell.

Reclassifies continuous raster values into discrete intervals or classes.

Estimates incoming solar radiation based on terrain, aspect, date, and atmospheric conditions.

Computes space-time kernel density over a raster.

Quantifies spatial association between neighboring zones from each zone's values.

Computes a spectral index by combining selected bands of an image.

Splits a raster into output files or tiles.

Computes the square root of each raster cell.

Raises each cell value to the power of two and outputs the transformed raster.

Estimates storage volume of depressions in an elevation model.

Counts pixels of each class in each slice of a multidimensional categorical raster.

Derives curvature, aspect, and shape parameters from a surface.

Calculates volume between a raster surface and a reference height.

Computes the tangent of each cell value and creates a transformed raster.

Computes the hyperbolic tangent of each raster cell.

Computes cross-correlation of time series over a raster.

Interpolates a surface using a triangulated irregular network (TIN).

Converts raster angular values from radians to degrees.

Converts raster angular values from degrees to radians.

Fits a polynomial surface representing the overall spatial trend.

Converts the trend surface into vector points with estimated values.

Removes the decimal part of each raster value, keeping only the integer component.

Simulates a random spatial field with a specified variogram structure.

Performs a two-sample KS test on a raster.

Warps a raster using control points to align it to a reference.

Builds Voronoi regions weighted by each point's influence.

Performs a Wilcoxon signed rank test on a raster.

Standardizes raster values as deviations from their global mean.

Summarizes raster properties within zones to characterize each spatial unit.

Fills NoData cells with values derived from defined zones.

Calculates area, perimeter, and other geometric measures for each raster zone.

Counts raster value frequencies within each zone, generating a per-zone histogram.

Summarizes raster values using zonal statistics.

Aggregates values in a multidimensional raster by dimension or interval to summarize data series.

Applies radiometric calibration to raster bands using sensor parameters.

Calculates statistics for the relative position of cells within a neighborhood or region.

Combines selected raster bands into a multiband image.

Calculates indices derived from synthetic-aperture radar (SAR) imagery.

Converts amplitude or backscatter units in SAR data.

Aligns rasters so their cells correspond spatially before analysis.

Calculates the return direction from each cell toward the lowest-cost source.

Calculates moving statistics along a dimension of a multidimensional raster.

Extracts ocean-wind estimates from Earth-observation raster products.

Extracts spectral signatures from selected pixels or regions of an image.

Corrects topographic or orbital phase in an interferogram for analysis.

Compares frequencies or amplitudes between images to detect differences.

Reduces interferogram phase noise with the Goldstein filter.

Merges multidimensional rasters while preserving compatible dimensions and variables.

Calculates principal components to reduce multidimensional raster dimensionality.

Calculates correlation between variables or slices of a multidimensional raster.

Estimates coherence between SAR observations from different dates.

Generates observation points to evaluate visibility or spatial relationships over terrain.

Normalizes SAR backscatter to compensate for terrain effects.

Combines regression and kriging to interpolate values with spatial trends and residuals.

Removes thermal noise from SAR imagery to improve useful signal.

Extracts selected dimensions, variables, or intervals from a multidimensional raster.

Unwraps interferogram phase to produce continuous values.

Generates a distance or influence zone raster around non-null cells of an input raster.

Assigns each cell to the source reachable at the lowest accumulated cost.

Computes minimum accumulated cost from each cell to the specified sources.

Traces least-cost paths from destinations to their sources over a surface.

Assigns each cell to the nearest source based on Euclidean distance.

Calculates straight-line distance from each cell to the nearest source.

Calculates local correlation between two images within neighbourhood windows.

Interpolates a surface from points by weighting natural neighbours of the triangulation.

Generates an interpolated surface using the nearest-neighbour method.

Adds two rasters, or a raster and a constant, cell by cell.

Combines rasters using an average overlay and outputs a raster of calculated values.

Computes the cell-wise logical conjunction between two raster conditions.

Inverts the logical value of each input raster cell.

Computes the cell-wise logical disjunction between two raster conditions.

Applies the XOR logical operation between two boolean rasters.

Counts per cell how many rasters in a stack meet a specified value or condition.

Divides two rasters, or a raster by a constant, cell by cell.

Identifies which layer in a stack contributes the highest value per cell.

Identifies which layer in a stack contributes the lowest value per cell.

Combines rasters using a maximum absolute overlay and outputs a raster of calculated values.

Combines rasters using a maximum overlay and outputs a raster of calculated values.

Combines rasters using a minimum absolute overlay and outputs a raster of calculated values.

Combines rasters using a minimum overlay and outputs a raster of calculated values.

Calculates the remainder of division between the values of two rasters.

Multiplies two rasters, or a raster and a constant, cell by cell.

Multiplies the values of several overlapping rasters to produce a combined surface.

Calculates the percentage of layers in a stack equal to a target value.

Calculates the percentage of layers in a stack greater than a target value.

Calculates the percentage of layers in a stack less than a target value.

Selects per cell the value from a list of rasters based on an index raster.

Raises raster values to a power, cell by cell.

Combines rasters using a standard deviation overlay and outputs a raster of calculated values.

Subtracts two rasters, or subtracts one from a constant, cell by cell.

Combines rasters using a sum overlay and outputs a raster of calculated values.

Replaces nodata cells with corresponding values from another raster.

Combines rasters using a weighted overlay and outputs a raster of calculated values.

Combines multiple rasters by multiplying each by its weight before summing.

Evaluates a condition between rasters and assigns each cell the value for the true or false result.

Reclassifies a raster into zones or classes according to defined rules.

Reclassifies a raster into equal-interval classes according to defined rules.

Fits a geographically weighted regression and outputs a raster of local relationships between variables.

Calculates Getis-Ord Gi* per cell to detect local high or low clusters.

Estimates a spatial intensity surface that can vary across zones.

Interpolates locally using only the point neighbourhood relevant to each location.

Calculates local Moran's I (LISA) on a raster.

Interpolates a surface assuming an unknown local mean and autocorrelation.

Interpolates a surface using a known mean and a variogram model.

Interpolates values across space and time considering spatial and temporal dependence.

Fits a raster regression that accounts for autocorrelation in the errors.

Fits a spatial lag regression; coefficients and predictions incorporate neighboring values.

Interpolates by modeling spatial trend plus residual autocorrelation.