LogoLogo
HomeAcademyLoginTry for free
  • Welcome
  • What's new
    • Q2 2025
    • Q1 2025
    • Q4 2024
    • Q3 2024
    • Q2 2024
    • Q1 2024
    • Q4 2023
    • Q3 2023
    • Q2 2023
    • Q1 2023
    • Q4 2022
    • Q3 2022
  • FAQs
    • Accounts
    • Migration to the new platform
    • User & organization setup
    • General
    • Builder
    • Workflows
    • Data Observatory
    • Analytics Toolbox
    • Development Tools
    • Deployment Options
    • CARTO Basemaps
    • CARTO for Education
    • Support Packages
    • Security and Compliance
  • Getting started
    • What is CARTO?
    • Quickstart guides
      • Connecting to your data
      • Creating your first map
      • Creating your first workflow
      • Developing your first application
    • CARTO Academy
  • CARTO User Manual
    • Overview
      • Creating your CARTO organization
      • CARTO Cloud Regions
      • CARTO Workspace overview
    • Maps
      • Data sources
        • Simple features
        • Spatial Indexes
        • Pre-generated tilesets
        • Rasters
        • Defining source spatial data
        • Managing data freshness
        • Changing data source location
      • Layers
        • Point
          • Grid point aggregation
          • H3 point aggregation
          • Heatmap point aggregation
          • Cluster point aggregation
        • Polygon
        • Line
        • Grid
        • H3
        • Raster
        • Zoom to layer
      • Widgets
        • Formula widget
        • Category widget
        • Pie widget
        • Histogram widget
        • Range widget
        • Time Series widget
        • Table widget
      • SQL Parameters
        • Date parameter
        • Text parameter
        • Numeric parameter
        • Publishing SQL parameters
      • Interactions
      • Legend
      • Basemaps
        • Basemap selector
      • AI Agents
      • SQL analyses
      • Map view modes
      • Map description
      • Feature selection tool
      • Search locations
      • Measure distances
      • Exporting data
      • Download PDF reports
      • Managing maps
      • Sharing and collaboration
        • Editor collaboration
        • Map preview for editors
        • Map settings for viewers
        • Comments
        • Embedding maps
        • URL parameters
      • Performance considerations
    • Workflows
      • Workflow canvas
      • Results panel
      • Components
        • Aggregation
        • Custom
        • Data Enrichment
        • Data Preparation
        • Generative AI
        • Input / Output
        • Joins
        • Parsers
        • Raster Operations
        • Spatial Accessors
        • Spatial Analysis
        • Spatial Constructors
        • Spatial Indexes
        • Spatial Operations
        • Statistics
        • Tileset Creation
        • BigQuery ML
        • Snowflake ML
        • Google Earth Engine
        • Google Environment APIs
        • Telco Signal Propagation Models
      • Data Sources
      • Scheduling workflows
      • Sharing workflows
      • Using variables in workflows
      • Executing workflows via API
      • Temporary data in Workflows
      • Extension Packages
      • Managing workflows
      • Workflows best practices
    • Data Explorer
      • Creating a map from your data
      • Importing data
        • Importing rasters
      • Geocoding data
      • Optimizing your data
    • Data Observatory
      • Terminology
      • Browsing the Spatial Data Catalog
      • Subscribing to public and premium datasets
      • Accessing free data samples
      • Managing your subscriptions
      • Accessing your subscriptions from your data warehouse
        • Access data in BigQuery
        • Access data in Snowflake
        • Access data in Databricks
        • Access data in Redshift
        • Access data in PostgreSQL
    • Connections
      • Google BigQuery
      • Snowflake
      • Databricks
      • Amazon Redshift
      • PostgreSQL
      • CARTO Data Warehouse
      • Sharing connections
      • Deleting a connection
      • Required permissions
      • IP whitelisting
      • Customer data responsibilities
    • Applications
    • Settings
      • Understanding your organization quotas
      • Activity Data
        • Activity Data Reference
        • Activity Data Examples
        • Activity Data Changelog
      • Users and Groups
        • Inviting users to your organization
        • Managing user roles
        • Deleting users
        • SSO
        • Groups
        • Mapping groups to user roles
      • CARTO Support Access
      • Customizations
        • Customizing appearance and branding
        • Configuring custom color palettes
        • Configuring your organization basemaps
        • Enabling AI Agents
      • Advanced Settings
        • Managing applications
        • Configuring S3 Bucket for Redshift Imports
        • Configuring OAuth connections to Snowflake
        • Configuring OAuth U2M connections to Databricks
        • Configuring S3 Bucket integration for RDS for PostgreSQL Exports in Builder
        • Configuring Workload Identity Federation for BigQuery
      • Data Observatory
      • Deleting your organization
    • Developers
      • Managing Credentials
        • API Base URL
        • API Access Tokens
        • SPA OAuth Clients
        • M2M OAuth Clients
      • Named Sources
  • Data and Analysis
    • Analytics Toolbox Overview
    • Analytics Toolbox for BigQuery
      • Getting access
        • Projects maintained by CARTO in different BigQuery regions
        • Manual installation in your own project
        • Installation in a Google Cloud VPC
        • Core module
      • Key concepts
        • Tilesets
        • Spatial indexes
      • SQL Reference
        • accessors
        • clustering
        • constructors
        • cpg
        • data
        • http_request
        • import
        • geohash
        • h3
        • lds
        • measurements
        • placekey
        • processing
        • quadbin
        • random
        • raster
        • retail
        • routing
        • s2
        • statistics
        • telco
        • tiler
        • transformations
      • Guides
        • Running queries from Builder
        • Working with Raster data
      • Release notes
      • About Analytics Toolbox regions
    • Analytics Toolbox for Snowflake
      • Getting access
        • Native App from Snowflake's Marketplace
        • Manual installation
      • Key concepts
        • Spatial indexes
        • Tilesets
      • SQL Reference
        • accessors
        • clustering
        • constructors
        • data
        • http_request
        • import
        • h3
        • lds
        • measurements
        • placekey
        • processing
        • quadbin
        • random
        • raster
        • retail
        • s2
        • statistics
        • tiler
        • transformations
      • Guides
        • Running queries from Builder
        • Working with Raster data
      • Release Notes
    • Analytics Toolbox for Databricks
      • Getting access
        • Personal (former Single User) cluster
        • Standard (former Shared) cluster
      • Reference
        • lds
        • tiler
      • Guides
      • Release Notes
    • Analytics Toolbox for Redshift
      • Getting access
        • Manual installation in your database
        • Installation in an Amazon Web Services VPC
        • Core version
      • Key concepts
        • Tilesets
        • Spatial indexes
      • SQL Reference
        • clustering
        • constructors
        • data
        • http_request
        • import
        • lds
        • placekey
        • processing
        • quadbin
        • random
        • s2
        • statistics
        • tiler
        • transformations
      • Guides
        • Running queries from Builder
      • Release Notes
    • Analytics Toolbox for PostgreSQL
      • Getting access
        • Manual installation
        • Core version
      • Key concepts
        • Tilesets
        • Spatial Indexes
      • SQL Reference
        • h3
        • quadbin
        • tiler
      • Guides
        • Creating spatial index tilesets
        • Running queries from Builder
      • Release Notes
    • CARTO + Python
      • Installation
      • Authentication Methods
      • Visualizing Data
      • Working with Data
        • How to work with your data in the CARTO Data Warehouse
        • How to access your Data Observatory subscriptions
        • How to access CARTO's Analytics Toolbox for BigQuery and create visualizations via Python notebooks
        • How to access CARTO’s Analytics Toolbox for Snowflake and create visualizations via Python notebooks
        • How to visualize data from Databricks
      • Reference
    • CARTO QGIS Plugin
  • CARTO for Developers
    • Overview
    • Key concepts
      • Architecture
      • Libraries and APIs
      • Authentication methods
        • API Access Tokens
        • OAuth Access Tokens
        • OAuth Clients
      • Connections
      • Data sources
      • Visualization with deck.gl
        • Basemaps
          • CARTO Basemap
          • Google Maps
            • Examples
              • Gallery
              • Getting Started
              • Basic Examples
                • Hello World
                • BigQuery Tileset Layer
                • Data Observatory Tileset Layer
              • Advanced Examples
                • Arc Layer
                • Extrusion
                • Trips Layer
            • What's New
          • Amazon Location
            • Examples
              • Hello World
              • CartoLayer
            • What's New
      • Charts and widgets
      • Filtering and interactivity
      • Integrating Builder maps in your application
      • Summary
    • Quickstart
      • Make your first API call
      • Visualize your first dataset
      • Create your first widget
    • Guides
      • Build a public application
      • Build a private application
      • Build a private application using SSO
      • Visualize massive datasets
      • Integrate CARTO in your existing application
      • Use Boundaries in your application
      • Avoid exposing SQL queries with Named Sources
      • Managing cache in your CARTO applications
    • Reference
      • Deck (@deck.gl reference)
      • Data Sources
        • vectorTableSource
        • vectorQuerySource
        • vectorTilesetSource
        • h3TableSource
        • h3QuerySource
        • h3TilesetSource
        • quadbinTableSource
        • quadbinQuerySource
        • quadbinTilesetSource
        • rasterSource
        • boundaryTableSource
        • boundaryQuerySource
      • Layers (@deck.gl/carto)
      • Widgets
        • Data Sources
        • Server-side vs. client-side
        • Models
          • getFormula
          • getCategories
          • getHistogram
          • getRange
          • getScatter
          • getTimeSeries
          • getTable
      • Filters
        • Column filters
        • Spatial filters
      • fetchMap
      • CARTO APIs Reference
    • Release Notes
    • Examples
    • CARTO for React
      • Guides
        • Getting Started
        • Views
        • Data Sources
        • Layers
        • Widgets
        • Authentication and Authorization
        • Basemaps
        • Look and Feel
        • Query Parameters
        • Code Generator
        • Sample Applications
        • Deployment
        • Upgrade Guide
      • Examples
      • Library Reference
        • Introduction
        • API
        • Auth
        • Basemaps
        • Core
        • Redux
        • UI
        • Widgets
      • Release Notes
  • CARTO Self-Hosted
    • Overview
    • Key concepts
      • Architecture
      • Deployment requirements
    • Quickstarts
      • Single VM deployment (Kots)
      • Orchestrated container deployment (Kots)
      • Advanced Orchestrated container deployment (Helm)
    • Guides
      • Guides (Kots)
        • Configure your own buckets
        • Configure an external in-memory cache
        • Enable Google Basemaps
        • Enable the CARTO Data Warehouse
        • Configure an external proxy
        • Enable BigQuery OAuth connections
        • Configure Single Sign-On (SSO)
        • Use Workload Identity in GCP
        • High availability configuration for CARTO Self-hosted
        • Configure your custom service account
      • Guides (Helm)
        • Configure your own buckets (Helm)
        • Configure an external in-memory cache (Helm)
        • Enable Google Basemaps (Helm)
        • Enable the CARTO Data Warehouse (Helm)
        • Configure an external proxy (Helm)
        • Enable BigQuery OAuth connections (Helm)
        • Configure Single Sign-On (SSO) (Helm)
        • Use Workload Identity in GCP (Helm)
        • Use EKS Pod Identity in AWS (Helm)
        • Enable Redshift imports (Helm)
        • Migrating CARTO Self-hosted installation to an external database (Helm)
        • Advanced customizations (Helm)
        • Configure your custom service account (Helm)
    • Maintenance
      • Maintenance (Kots)
        • Updates
        • Backups
        • Uninstall
        • Rotating keys
        • Monitoring
        • Change the Admin Console password
      • Maintenance (Helm)
        • Monitoring (Helm)
        • Rotating keys (Helm)
        • Uninstall (Helm)
        • Backups (Helm)
        • Updates (Helm)
    • Support
      • Get debug information for Support (Kots)
      • Get debug information for Support (Helm)
    • CARTO Self-hosted Legacy
      • Key concepts
        • Architecture
        • Deployment requirements
      • Quickstarts
        • Single VM deployment (docker-compose)
      • Guides
        • Configure your own buckets
        • Configure an external in-memory cache
        • Enable Google Basemaps
        • Enable the CARTO Data Warehouse
        • Configure an external proxy
        • Enable BigQuery OAuth connections
        • Configure Single Sign-On (SSO)
        • Enable Redshift imports
        • Configure your custom service account
        • Advanced customizations
        • Migrating CARTO Self-Hosted installation to an external database
      • Maintenance
        • Updates
        • Backups
        • Uninstall
        • Rotating keys
        • Monitoring
      • Support
    • Release Notes
  • CARTO Native App for Snowflake Containers
    • Deploying CARTO using Snowflake Container Services
  • Get Help
    • Legal & Compliance
    • Previous libraries and components
    • Migrating your content to the new CARTO platform
Powered by GitBook
On this page
  • Layer options
  • Visualization types
  • Visibility by zoom level
  • Aggregate by geometry
  • Layer styling
  • Color palettes
  • Color schema by HexColor
  • Color Scale
  • 3D visualization using Height
  • Layer blending

Was this helpful?

Export as PDF
  1. CARTO User Manual
  2. Maps

Layers

PreviousChanging data source locationNextPoint

Last updated 2 months ago

Was this helpful?

Layers in Builder are connected to data sources and are used to render features on a map by directly connecting to your data warehouse. Once a data source is added to Builder, a layer is automatically added for that data source. If the spatial definition is valid, the features will be rendered on the map. Learn more about defining source spatial data in this .

Layer options

When working with layers in Builder, you have the following options:

  • Zoom to: Zoom to the layer extent, taking into account any filtering applied in Widgets and/or Parameters when applicable.

  • Show only this/Show all layers: Easily set layers visibility on and off.

  • Layer style: Access the layer panel to set your layer styling configuration.

  • Duplicate layer: Duplicate a layer with the same styling properties.

  • Rename: Edit the name of your layer.

  • Delete: Remove the layer and its corresponding source.

Visualization types

The spatial definition of the source linked to a layer specifies the layer visualization type and additional visualization and styling options. The different layer visualization types supported in Buider are:

  • : Displays as point geometries. Point data can be dynamically aggregated to the following types:

    • : Aggregated point geometry to grid.

    • : Aggregated point geometry to hexagonal cells.

    • : Aggregated point geometry by density.

    • : Aggregated point geometry by circles.

  • : Displays as polygon geometries.

  • : Displays as line geometries.

  • : Displays features as grid cells.

  • : Displays features as hexagon cells.

  • : Displays a grid of pixels.

Visibility by zoom level

Control the zoom range where a layer should be visibile. This is useful for combining different type of sources, such as aggregated data for lower zoom levels and non-aggregated data for higher levels or visualizing different administrative levels.

Aggregate by geometry

If you are working with point, polygon or line layer visualization types containing identical geometries with varying attributes (e.g., weather stations or buildings), you can use the Aggregate by geometry functionality to aggregate your layer based on a distinct spatial column. This allows you to:

  • Aggregate geometries in your layer ensuring an optimal performance.

  • Aggregate styling and interaction attributes to retrieve relevant information link to your aggregated feature.

  • Maintain widgets functionality over the original source, enabling drill-down operations for deeper insights.

Layer styling

Layer styling is essential for making your maps informative and engaging. Below are generic aspects of visualization and styling options available in Builder. For more detailed styling capabilities for a specific layer type, we recommend to check each layer type as defined above.

Color palettes

When styling layers in Builder, you can choose a few different types of color palettes:

  • Diverging: Highlight values that are above and below an interesting mid-point in quantitative data. This is a great way to show data values that differ greatly from the norm. For example, you may use a diverging colour scheme to show population change.

  • Sequential: Ideal for data that follows an order, often numeric ranging from low to high. For example, you may use a sequential colour scheme to show counts within a H3 grid.

  • Qualitative: Represents different categories of data. For example, a qualitative scheme is a good choice for showing different types of Points of Interest.

  • Singlehue: Gradual transition of a single color from light to dark. For example to visualize the quality network coverage signal.

  • Custom: Pick a new color either by clicking on the color picker or inputting HEX/RGB values. Color steps can be added, removed and shuffled.

Connections to Redshift clusters only support aggregation of categorical properties by any value.

Admins can also create custom color palettes from the organization settings. These are reusable color schemes and they are available to the whole organization, removing the need to define a new custom palette every time a custom set of colours is used for styling.

Color schema by HexColor

You can also tap into the HexColor feature to style qualitative data using the hex color codes from either your table or SQL query source. To harness this capability:

  1. Navigate to the Color based on selector and choose the text column you want to associate with the hex color code.

  2. In the Palette section, select the 'HexColor' option.

  3. Finally, choose the column containing the hex color code values.

Pre-generated tileset layers styled with HexColor are not currently supported in the legend. If you require this functionality, please provide feedback through your CARTO point of contact.

Color Scale

Depending on the property selected to define your color schema, you have different color scale functionalities to define the color classification method.

For numeric columns, you can choose the following data classification methods:

  • Quantile: A quantile color scale is determined by rank. A quantile classification is well suited to linearly distributed data. Each quantile class contains an equal number of features. There are no empty classes or classes with too few or too many values. This can be misleading sometimes, since similar features can be placed in adjacent classes or widely different values can be in the same class, due to equal number grouping.

  • Quantize: A quantized color scale is determined by grouping values in discrete increments. It allows to transform an initially continuous range into a discrete set of classes. Quantize scales will slice the domain’s extent into intervals of roughly equal lengths.

  • Custom: A custom color scale is determined by arbitrary breaks in the classification. A custom scale is well suited to tweak color ramps, adjusting the values to fine tune the visualizations.

For text columns, you can use the Ordinal classification method to set a specific category to each color value:

3D visualization using Height

Builders allows you to assign heights to build 3D visualization for both polygons and spatial index sources. You can activate this option in the Height section, using the slider to define a fix value or using a property to define the height.

When using the Height functionality, remember to activate the 3D view located in the toolbar above the map. Using this, you can achieve stunning visualizations as per below map.

Layer blending

Layer blending is a technique used to determine how overlapping features in different layers interact in terms of their visual representation. When two layers are blended, you can select the following blending options:

  • Additive: This mode adds the color values of overlapping features. When two colors are added together, the resulting color is often lighter. This blending mode is commonly used to visualize densities or intensities.

  • Subtractive: This blending mode subtracts the color values of the upper layer from the layer beneath it. The result is typically a darker color. In some contexts, this mode can help emphasize differences between layers.

When working with , you will need to select an aggregation operation for your columns.

For more information, see our .

For more information about how to leverage this functionality see this .

Logarithmic: A Logarithmic scale based on powers of 10 will be created automatically, based on the number of steps in the selected color palette. Logarithmic scales tend to work well with .

section
Point
Grid
H3
Heatmap
Cluster
Polygon
Line
Grid
H3
Raster
aggregated data sources
article on custom color palettes
tutorial
aggregated data sources
Explore a map with 3D polygons whose height is defined by the number of floors.