Workflow blocks are the building components of Atlas workflows. Each block performs a specific operation on your data. Blocks are organized into categories based on their function.
Import
Import blocks bring data into your workflow from various sources.
- Dataset: Use datasets already stored in your project
- Satellite Import: Import satellite imagery from providers
- API Import: Fetch data from external APIs
- AOI Input: Define area of interest inputs for spatial filtering
Integrations
Integration blocks connect to third-party data sources and services.
- OpenStreetMap: Import data from OpenStreetMap
- Overture Maps: Access Overture Maps datasets
Geoprocessing
Geoprocessing blocks perform fundamental spatial operations on features.
- Boundary: Convert filled shapes into outlines
- Buffer: Expand features by a set distance
- Clip: Cut features to a boundary
- Difference: Find areas in one layer but not another
- Intersection: Find where layers overlap
- Subtract: Remove overlapping areas
- Union: Combine multiple geometries
- Wedge Buffer: Create directional buffer zones
Boundary
The Boundary block converts filled polygon geometries into their outline representations. It extracts the outer and inner rings of polygons as line features.
Use this block when you need to work with polygon edges rather than filled areas. Common applications include digitizing boundaries or analyzing perimeters.
Buffer
The Buffer block expands features by a specified distance in all directions. It creates circular or rectangular zones around points, lines, or polygons.
Set the buffer distance using the distance parameter. Choose between meters, kilometers, miles, or feet as the unit of measurement.
Use buffers to create proximity zones, safety areas, or influence regions around features.
Clip
The Clip block cuts input features to the boundary of a clipping geometry. Features outside the boundary are removed while features crossing the boundary are trimmed.
Connect the features to clip to the primary input and the clipping boundary to the secondary input.
Use clipping to extract data for specific areas of interest or remove features outside study boundaries.
Difference
The Difference block finds areas present in the first input but not in the second input. It removes overlapping portions from the first dataset.
This operation is useful for exclusion analysis or removing protected areas from development zones.
Intersection
The Intersection block finds where two or more layers overlap. It returns only the geometric areas shared by all inputs.
Use intersection to identify areas meeting multiple criteria or to find features present in all input layers.
Subtract
The Subtract block removes overlapping areas between layers. It is similar to Difference but designed for specific subtraction workflows.
Use this block to exclude zones from larger areas or remove specific features from datasets.
Union
The Union block combines multiple geometries into a single merged feature. All input features become part of one unified geometry.
Use union to merge administrative boundaries, combine study areas, or create complete coverage from multiple sources.
Wedge Buffer
The Wedge Buffer block creates directional buffer zones in a specific angular direction. You define the bearing and angular width of the wedge.
Use wedge buffers for line-of-sight analysis, directional influence zones, or sector-based proximity analysis.
Geometry
Geometry blocks manipulate and transform feature geometries.
- Centroid: Find center points of features
- Fill Holes: Remove holes in polygons
- Lines to Polygon: Convert line features to polygons
- Explode MultiFeatures: Split multi-part features
- Explode Linestrings: Break lines into segments
- Polygon to Lines: Convert polygon boundaries to lines
- Remove duplicates: Clean duplicate features
- Generate Points Along Line: Create evenly spaced points
- Simplify: Reduce geometry complexity
- Smoothing: Smooth angular geometries
- Split by line: Divide features using a line
- Points to Geometry: Create geometries from points
Centroid
The Centroid block calculates the geometric center point of each feature. For polygons, it returns the center of mass. For lines, it returns the midpoint.
Use centroids to create point representations of polygons or to find center locations for labeling.
Fill Holes
The Fill Holes block removes interior holes from polygon geometries. It converts donut-shaped polygons into solid filled polygons.
Use this block to clean topology or simplify geometries for analysis that doesn't require hole preservation.
Lines to Polygon
The Lines to Polygon block converts closed line features into polygon features. Lines must form closed loops to create valid polygons.
Use this block when digitizing boundaries as lines that need conversion to polygons for area-based analysis.
Explode MultiFeatures
The Explode MultiFeatures block splits multi-part geometries into individual single-part features. Each component becomes a separate feature in the output.
Use this block to separate grouped features or prepare data for per-feature analysis.
Explode Linestrings
The Explode Linestrings block breaks line features into individual segments at each vertex. Each line segment becomes a separate feature.
Use this block for detailed line analysis or to process individual segments independently.
Polygon to Lines
The Polygon to Lines block converts polygon boundaries into line features. Both outer boundaries and interior holes become separate lines.
Use this block to extract boundaries for line-based analysis or to digitize polygon edges.
Remove Duplicates
The Remove Duplicates block identifies and removes duplicate features from a dataset. Features with identical geometries and attributes are consolidated.
Use this block to clean data and eliminate redundant features before analysis.
Generate Points Along Line
The Generate Points Along Line block creates evenly spaced points along line features. Specify the distance between points to control point density.
Use this block to sample lines at regular intervals or create analysis points along linear features.
Simplify
The Simplify block reduces the number of vertices in geometries while preserving overall shape. Set a tolerance value to control simplification strength.
Use simplification to reduce file sizes, improve rendering performance, or generalize detailed geometries.
Smoothing
The Smoothing block removes angular corners from geometries by applying smoothing algorithms. It creates more natural, flowing shapes.
Use smoothing to improve visual appearance of digitized features or create generalized boundaries.
Split by Line
The Split by Line block divides polygon features using one or more line features. The line acts as a cutting tool that separates polygons into multiple parts.
Use this block to subdivide parcels, split administrative boundaries, or divide study areas.
Points to Geometry
The Points to Geometry block creates lines or polygons from point features. Connect points in sequence to form the output geometry.
Use this block to digitize features from point data or create routes from waypoints.
Analysis
Analysis blocks perform advanced spatial analysis operations.
- Count Features in Surface: Count points in polygons
- Spatial Aggregation: Group and summarize spatial data
- Nearest Neighbour: Find closest features
- Voronoi Polygons: Create Thiessen polygons
- H3: Hexagonal hierarchical spatial indexing
- Cluster Analysis: Identify spatial clusters
- Hotspot Analysis: Detect statistically significant hotspots
- Shortest Distance: Calculate minimum distances
Count Features in Surface
The Count Features in Surface block counts how many point features fall within each polygon. It adds a count field to the polygon dataset.
Use this block for density analysis, aggregation, or spatial summary statistics.
Spatial Aggregation
The Spatial Aggregation block groups features by spatial relationship and summarizes their attributes. You can aggregate by containment, intersection, or proximity.
Use this block to summarize statistics for spatial groups like counting features per region or averaging values per zone.
Nearest Neighbour
The Nearest Neighbour block finds the closest feature from one dataset to each feature in another dataset. It calculates distance and identifies the nearest match.
Use this block for proximity analysis, closest facility finding, or spatial matching.
Voronoi Polygons
The Voronoi Polygons block creates polygons around points where each polygon contains the area closest to its point. These are also called Thiessen polygons.
Use Voronoi polygons for service area analysis, territory assignment, or spatial interpolation.
H3
The H3 block implements Uber's hexagonal hierarchical spatial index. It converts features to H3 hexagons at various resolutions.
Use H3 for consistent spatial binning, hierarchical aggregation, or analysis requiring hexagonal grids.
Cluster Analysis
The Cluster Analysis block identifies groups of features with similar spatial or attribute characteristics. It uses clustering algorithms to detect patterns.
Use this block to find natural groupings in data or identify spatially concentrated phenomena.
Hotspot Analysis
The Hotspot Analysis block detects statistically significant clusters of high or low values. It uses the Getis-Ord Gi* statistic to identify hotspots and coldspots.
Use this block to find significant spatial patterns or identify areas requiring intervention.
Shortest Distance
The Shortest Distance block calculates the minimum distance from each feature to the nearest feature in another dataset. It measures edge-to-edge distance.
Use this block for accessibility analysis, buffer verification, or proximity measurements.
Constructors
Constructor blocks generate new spatial features from parameters.
- Grid: Create regular grids
- Random Points Along Line: Generate random points on lines
- Random Points Inside Polygon: Generate random points in polygons
Grid
The Grid block creates regular square or hexagonal grids covering a specified extent. Set cell size to control grid resolution.
Use grids for spatial binning, sampling frameworks, or creating uniform analysis units.
Random Points Along Line
The Random Points Along Line block generates randomly positioned points along line features. Specify the number of points to create.
Use this block for random sampling of linear features or creating varied point distributions.
Random Points Inside Polygon
The Random Points Inside Polygon block generates randomly positioned points within polygon boundaries. Specify point count per polygon.
Use this block for random sampling within areas or creating point datasets for testing.
Data Management
Data Management blocks organize and process tabular and spatial data.
- Dissolve: Merge features by attribute
- Merge Layers: Combine multiple datasets
- Spatial Join: Join attributes based on location
- Vector to Raster: Convert vector to raster format
- Filter By Attribute: Select features by attribute values
- Filter by spatial: Select features by spatial relationship
- Table Join: Join datasets by common field
- Raster to Vector: Convert raster to vector format
- Filter Columns: Select specific columns
- Drop Columns: Remove columns from dataset
- Sort by attribute: Order features by field values
- Limit rows: Restrict number of output features
Dissolve
The Dissolve block merges features that share common attribute values. Adjacent features with the same dissolve field value are combined into single features.
Use dissolve to simplify data by aggregating features or to create regional summaries.
Merge Layers
The Merge Layers block combines multiple datasets with compatible geometries into a single output dataset. All features from all inputs are included.
Use this block to consolidate data from multiple sources or combine related datasets.
Spatial Join
The Spatial Join block joins attributes from one dataset to another based on spatial relationships. Features gain attributes from overlapping or nearby features.
Use spatial joins to enrich data with information from other layers or transfer attributes spatially.
Vector to Raster
The Vector to Raster block converts vector features into raster format. Specify cell size and the attribute to use for raster values.
Use this block to prepare vector data for raster analysis or create continuous surfaces from discrete features.
Filter By Attribute
The Filter By Attribute block selects features matching specified attribute criteria. Build queries using operators like equals, greater than, or contains.
Use this block to extract subsets of data or remove unwanted features before analysis.
Filter by Spatial
The Filter by Spatial block selects features based on spatial relationships with another dataset. Choose relationships like intersects, contains, or within.
Use this block to extract features in specific locations or meeting spatial criteria.
Table Join
The Table Join block joins two datasets based on a common field. Features in the primary dataset gain attributes from matching features in the join dataset.
Use this block to enrich data with information from external tables or combine related datasets.
Raster to Vector
The Raster to Vector block converts raster data into vector features. Each unique raster value becomes a separate polygon.
Use this block to extract features from classified rasters or convert analysis results to vector format.
Filter Columns
The Filter Columns block keeps only specified columns in the output dataset. All other columns are removed.
Use this block to reduce data size or focus on specific attributes for analysis.
Drop Columns
The Drop Columns block removes specified columns from the dataset. All other columns are retained.
Use this block to clean data by removing unnecessary fields or sensitive information.
Sort by Attribute
The Sort by Attribute block orders features based on attribute values. Sort in ascending or descending order.
Use this block to rank features or prepare data for sequential processing.
Limit Rows
The Limit Rows block restricts the number of features in the output. Specify the maximum number of features to keep.
Use this block to create sample datasets or prevent processing too many features.
Terrain Analysis
Terrain Analysis blocks process digital elevation models to extract terrain characteristics.
- Aspect Analysis: Calculate terrain aspect
- Contour: Generate elevation contour lines
- Hillshade: Create shaded relief
- Slope Analysis: Calculate terrain slope
Aspect Analysis
The Aspect Analysis block calculates the compass direction that terrain faces. It produces a raster where each cell contains the aspect in degrees.
Use aspect analysis for solar exposure modeling, watershed analysis, or terrain characterization.
Contour
The Contour block generates elevation contour lines from a digital elevation model. Specify contour interval to control line spacing.
Use contours for topographic mapping, terrain visualization, or elevation representation.
Hillshade
The Hillshade block creates shaded relief from elevation data. It simulates shadows cast by terrain based on sun position.
Use hillshade for terrain visualization, basemap creation, or enhancing elevation representation.
Slope Analysis
The Slope Analysis block calculates terrain steepness from elevation data. Output values represent slope in degrees or percent.
Use slope analysis for stability assessment, development suitability, or terrain classification.
Raster Operations
Raster Operations blocks perform advanced processing on raster data.
- Binary Classification: Classify raster into two categories
- Crop Raster: Clip raster to boundary
- Distance Raster: Calculate distance from features
- Point Extraction: Extract raster values at points
- Zonal Statistics: Summarize raster values within polygons
- Reclassify: Remap raster values
- Interpolate: Create continuous surface from points
- Smooth Raster: Apply smoothing filters
- Band Arithmetic: Perform calculations across raster bands
- Resample Raster: Change raster resolution
- Resample by Factor: Resize raster by multiplication factor
Binary Classification
The Binary Classification block classifies raster cells into two categories based on a threshold value. Cells above the threshold receive one value while cells below receive another.
Use binary classification to create masks, identify areas above thresholds, or simplify continuous rasters.
Crop Raster
The Crop Raster block clips raster data to a polygon boundary. Cells outside the boundary are removed from the output.
Use this block to extract raster data for study areas or remove data outside regions of interest.
Distance Raster
The Distance Raster block calculates the distance from each raster cell to the nearest feature in a vector dataset. Output is a continuous distance surface.
Use distance rasters for proximity analysis, accessibility modeling, or cost surface creation.
Point Extraction
The Point Extraction block extracts raster values at point locations. Each point gains an attribute containing the underlying raster value.
Use this block to sample rasters at specific locations or extract elevation at survey points.
Zonal Statistics
The Zonal Statistics block summarizes raster values within polygon zones. Calculate statistics like mean, sum, minimum, or maximum per polygon.
Use zonal statistics to aggregate raster data by administrative units or summarize continuous data by region.
Reclassify
The Reclassify block remaps raster values according to a reclassification table. Define ranges of input values and their corresponding output values.
Use reclassification to simplify continuous data, create categories, or standardize raster values.
Interpolate
The Interpolate block creates continuous raster surfaces from point measurements. Choose from methods like IDW, kriging, or spline.
Use interpolation to estimate values between measurements or create surfaces from sample points.
Smooth Raster
The Smooth Raster block applies smoothing filters to reduce noise in raster data. It averages cell values with their neighbors.
Use smoothing to reduce artifacts, generalize data, or improve visual appearance.
Band Arithmetic
The Band Arithmetic block performs mathematical operations across raster bands. Create custom formulas using band values and operators.
Use band arithmetic to calculate indices like NDVI, combine bands, or derive new raster products.
Resample Raster
The Resample Raster block changes raster resolution by specifying a new cell size. Choose resampling methods like nearest neighbor or bilinear.
Use resampling to match raster resolutions or reduce file sizes.
Resample by Factor
The Resample by Factor block resizes rasters by multiplying or dividing the current cell size by a factor. Values greater than one decrease resolution while values less than one increase it.
Use this block for quick resolution changes without calculating exact cell sizes.
Analysis Tools
Analysis Tools blocks provide specialized analysis capabilities.
- Travel Time Analysis: Calculate isochrones and travel time zones
Travel Time Analysis
The Travel Time Analysis block calculates isochrones showing areas reachable within specified travel times. It uses road networks and routing algorithms.
Configure travel mode, maximum travel time, and departure location. The block generates polygons representing reachable areas.
Use this block for accessibility analysis, service area delineation, or catchment area mapping.
AI Tools
AI Tools blocks leverage machine learning and artificial intelligence for advanced operations.
- Segment Anything Model: AI-powered image segmentation
- SolarEye: Solar panel detection and analysis
- AI Column: Generate AI-powered field values
Segment Anything Model
The Segment Anything Model block uses Meta's SAM model to segment objects in imagery automatically. It detects and delineates objects without training data.
Connect imagery to the input and specify segmentation parameters. The block outputs polygons representing detected objects.
Use this block for automated feature extraction, object detection, or rapid digitization.
SolarEye
The SolarEye block detects solar panels in aerial or satellite imagery. It identifies panel locations and calculates area and capacity estimates.
Connect imagery covering buildings or installations. The block outputs polygons representing detected solar panels with attributes.
Use this block for renewable energy assessment, solar installation mapping, or capacity analysis.
AI Column
The AI Column block generates attribute values using AI language models. Provide prompts describing the values to generate and the block creates content for each feature.
Use this block to enrich data with AI-generated descriptions, classifications, or derived information.
Export
Export blocks save workflow results to your project or external destinations.
- Save as dataset: Store output in project or workspace datasets
Save as Dataset
The Save as Dataset block stores workflow output as a permanent dataset in your project. Choose to create a new dataset or overwrite an existing one.
Specify the dataset name and destination workspace. The saved dataset becomes available in your project's Layers Panel.
Use this block to preserve workflow results, share outputs with team members, or prepare data for use in other workflows.
