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mapbox/tippecanoe

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3,026 stars·426 forks·C++·bsd-2-clause·20 views

Tippecanoe

Tippecanoe is a command-line tool used to generate optimized vector tiles for web maps. It converts large-scale geospatial datasets, including GeoJSON, CSV, and Geobuf files, into binary vector tiles or MBTiles SQLite databases.

The project is designed to maintain map performance and visual quality across different zoom levels. It achieves this through geospatial data downsampling, which includes simplifying geometries and thinning point density to prevent tile overcrowding and keep tile sizes within specific limits.

The tool provides extensive data transformation capabilities, such as attribute-based filtering, feature coalescing, and point clustering. It also supports merging multiple geospatial sources and joining external CSV attributes to existing tile features.

Tippecanoe includes utilities for projecting coordinates from WGS84 to Web Mercator and sorting features via a Hilbert Curve to optimize spatial data layout.

Features

  • Vector Tile Generation - Transforms geospatial data in Geobuf format into vector tiles by projecting coordinates and processing geometry.
  • Geospatial Data Downsamplers - Simplifies geometries and thins point density to maintain map performance across different zoom levels.
  • Vector Tile Conversion - Transforms geospatial coordinates into tiled vector formats by decoding geometry and scaling zoom levels.
  • Map Data Optimizers - Simplifies geometries and clusters point features to keep tile sizes small while maintaining visual detail.
  • Binary Serialization - Encodes geospatial coordinates and attributes into a compact binary format for efficient transmission and storage.
  • Feature Downsampling - Thins point data and simplifies geometries at lower zoom levels to prevent tile overcrowding.
  • GeoJSON to Vector Tile Conversion - Parse GeoJSON features and geometries from input files to generate optimized vector tiles.
  • Geospatial Feature Deserialization - Reads binary geospatial data to reconstruct features, including geometry, attributes, and layer associations.
  • Geospatial Format Parsing - Translates GeoJSON, CSV, and Geobuf inputs into a unified internal representation for projection and tiling.
  • Geospatial Tile Processors - Converts between geographic coordinates and tiled representations for mapping data to the correct tile locations.
  • Large Scale Map Tiling - Processes massive GeoJSON, CSV, or Geobuf files into MBTiles or directory structures for geographic information systems.
  • MBTiles Packaging - Stores generated vector tiles and metadata within a single SQLite database following the MBTiles specification.
  • Point Data Downsampling - Drops a fraction of point features at lower zoom levels to prevent tile overcrowding.
  • MBTiles Storage Adapters - Packages generated geospatial tiles and metadata into a SQLite database following the MBTiles specification.
  • Geospatial Feature Serialization - Writes geospatial geometry and metadata into a binary format optimized for efficient storage and retrieval.
  • Geometry Simplification Tools - Reduces vertex density of lines and polygons using adjustable tolerances to maintain visual fidelity.
  • Geospatial Vector Simplification - Reduces the complexity of lines and polygons using adjustable tolerances to maintain performance across zoom levels.
  • Geospatial Data Downsampling - Reduces the complexity of lines and points across zoom levels to prevent map overcrowding and slow performance.
  • Vector Tile Generation - Converts large geospatial datasets into optimized vector tiles for efficient web map rendering.
  • Vector Tile Generators - Converts GeoJSON, CSV, and Geobuf data into optimized binary vector tiles for web maps.
  • Coordinate Projections - Handles input data in WGS84 or Web Mercator projections to ensure correct placement in vector tiles.
  • Coordinate-to-Tile Mapping - Transforms geospatial coordinates and projections into tile indices and back to map coordinates.
  • Geographic Projections - Transforms geographic coordinates from WGS84 ellipsoidal models to a flat Web Mercator plane for indexing.
  • CSV to Vector Tile Conversion - Parse geospatial data from CSV files and integrate it into a vector tile structure.
  • JSON and Data Parsing - Convert JSON-formatted geospatial data into internal representations of points, lines, and polygons.
  • Tileset Merging - Join multiple tile files or directories together with layer renaming and selective zoom level copying.
  • Unique Identifier Generators - Implements utilities to generate unique IDs for geospatial features or map existing attributes as primary identifiers.
  • Geobuf Parsing - Convert Geobuf encoded geospatial data into a format suitable for vector tile generation.
  • Attribute Filtering - Includes or excludes geospatial features based on logic filters or specific attribute values.
  • Disk-Based Tile Storage - Saves geospatial data as a directory hierarchy of binary files organized by zoom and coordinates.
  • Feature Attribute Management - Provides tools to include, exclude, or coerce data types for attributes and assign custom metadata descriptions.
  • Feature Coalescing - Merges multiple point features into MultiPoint features to reduce the total number of elements in a tile.
  • Geospatial Source Merging - Combine multiple geospatial input files into a single layer or maintain them as separate layers.
  • Shell-Based Processing - Execute shell commands as pre- or post-filters to transform geospatial features during tiling.
  • Vector Tile Feature Transformation - Filters, merges, and modifies geospatial features using shell commands and attribute-based logic.
  • Feature Filtering Pipelines - Executes external system commands as pre- or post-processing steps to transform geospatial attributes.
  • Spatial Data Preprocessing - Cleans and transforms geospatial attributes and coordinates using shell filters before tiling them for a map.
  • MBTiles Database Generation - Packages geospatial vector data into the MBTiles SQLite format for efficient storage and serving.
  • Vector Tile Density Management - Thins out features using dot-density gamma or reduction strategies to prevent tile overcrowding.
  • Vector Tile Size Constraints - Drops or coalesces features dynamically to ensure compressed tiles stay under specific byte or feature count limits.
  • Geospatial Geometry Clipping - Implements geometry clipping to limit the geographic extent of generated tiles to a specified bounding box.
  • Vector Tile Merging - Combine multiple vector tile sources into a single output by joining layers and filtering attributes.
  • Map Point Clustering - Groups nearby points into single representative features and aggregates attributes using mathematical operations.
  • Spatial Sorting - Orders geospatial features along a space-filling Hilbert curve to optimize disk access and locality.
  • C Geospatial Libraries - Tool for building vector tilesets from large GeoJSON collections.
  • Low Level Geospatial Libraries - Builds vector tilesets from large feature collections.
  • Visualization Frameworks - Build vector tilesets from large GeoJSON collections.

Star history

Star history chart for mapbox/tippecanoeStar history chart for mapbox/tippecanoe

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Frequently asked questions

What does mapbox/tippecanoe do?

Tippecanoe is a command-line tool used to generate optimized vector tiles for web maps. It converts large-scale geospatial datasets, including GeoJSON, CSV, and Geobuf files, into binary vector tiles or MBTiles SQLite databases.

What are the main features of mapbox/tippecanoe?

The main features of mapbox/tippecanoe are: Vector Tile Generation, Geospatial Data Downsamplers, Vector Tile Conversion, Map Data Optimizers, Binary Serialization, Feature Downsampling, GeoJSON to Vector Tile Conversion, Geospatial Feature Deserialization.

Which projects share features with mapbox/tippecanoe?

Projects with overlapping indexed features include: mbloch/mapshaper — Mapshaper is a tool for processing, simplifying, and converting geographic vector data, available as a command-line… maplibre/martin — Martin is a geospatial data API and vector tile server that delivers map tiles, styles, sprites, and glyphs to web map… urbica/martin — Martin is a vector tile server and map asset server that delivers geospatial data from PostGIS databases, MBTiles, and… toblerity/shapely — Shapely is a geometric analysis library for the manipulation and analysis of planar geometric objects. It functions as… google/protobuf — Protocol Buffers is a binary serialization framework used to encode structured information into compact payloads to… golang/protobuf — This project is a Protocol Buffers implementation for Go, providing a binary serialization framework to convert native…

Projects sharing features with Tippecanoe

These projects share indexed features with Tippecanoe. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • mbloch/mapshapermbloch avatar

    mbloch/mapshaper

    4,133View on GitHub↗

    Mapshaper is a tool for processing, simplifying, and converting geographic vector data, available as a command-line interface, a web browser tool, and a Node.js library. It functions as a coordinate projector, vector data converter, and web map asset optimizer designed to transform spatial datasets between different coordinate reference systems and file formats. The project is distinguished by its topology-preserving geometry simplification, which reduces vertex counts while maintaining shared boundaries to prevent gaps and overlaps. It further optimizes assets for the web through coordinate

    JavaScript
    View on GitHub↗4,133
  • maplibre/martinmaplibre avatar

    maplibre/martin

    3,717View on GitHub↗

    Martin is a geospatial data API and vector tile server that delivers map tiles, styles, sprites, and glyphs to web map clients. It functions as a PostGIS vector tile server, generating tiles directly from databases, as well as serving data from MBTiles and PMTiles files. The project distinguishes itself through a specialized command line interface for managing MBTiles archives, allowing users to validate, compare, and merge offline map data. It also provides dynamic map styling capabilities, including the generation of signed distance field sprites for runtime recoloring and the on-the-fly pr

    Rusthacktoberfestleafletmapbox-gl
    View on GitHub↗3,717
  • urbica/martinurbica avatar

    urbica/martin

    3,707View on GitHub↗

    Martin is a vector tile server and map asset server that delivers geospatial data from PostGIS databases, MBTiles, and PMtiles files. It functions as a TileJSON metadata provider and a suite of vector tile tooling for generating, validating, and exporting geospatial tile archives. The project distinguishes itself by providing integrated map asset management, generating map styles, sprite sheets, and font glyphs on the fly. It supports advanced visual rendering capabilities such as Signed Distance Field sprites for runtime recoloring and fallback-based font composition to ensure complete chara

    Rust
    View on GitHub↗3,707
  • toblerity/shapelyToblerity avatar

    Toblerity/Shapely

    4,457View on GitHub↗

    Shapely is a geometric analysis library for the manipulation and analysis of planar geometric objects. It functions as a computational geometry toolkit, a spatial predicate engine for evaluating topological relationships, and a vectorized geometry processor. The library distinguishes itself through a vectorized geometry processor capable of executing operations across coordinate arrays with multi-threaded parallel processing. It utilizes prepared geometry optimization to accelerate repeated containment and intersection tests and implements R-tree spatial indexing for efficient nearest-neighbo

    Python
    View on GitHub↗4,457
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