geobase 0.3.1

Geospatial data structures, projections, tiling schemes and vector data support (GeoJSON, WKT, WKB).

Geospatial data structures (coordinates, geometries, features, metadata), projections and tiling schemes. Vector data format support for GeoJSON, WKT and WKB.

Features

✨ New: Data structures for simple geometries, features and feature collections. ✨ New: Support for Well-known binary (WKB). Text and binary data formats, encodings and content interfaces also redesigned.

Key features:

• 🌐 geographic (longitude-latitude) and projected positions and bounding boxes
• 🧩 simple geometries (point, line string, polygon, multi point, multi line string, multi polygon, geometry collection)
• 🔷 features (with id, properties and geometry) and feature collections
• 📅 temporal data structures (instant, interval) and spatial extents
• 📃 vector data formats supported (GeoJSON, WKT, WKB )
• 🗺️ coordinate projections (web mercator + based on the external proj4dart library)
• 🔢 tiling schemes and tile matrix sets (web mercator, global geodetic)

Usage

The package requires at least Dart SDK 2.17, and it supports all Dart and Flutter platforms.

Add the dependency in your pubspec.yaml:

dependencies:
  geobase: ^0.3.0

Import it:

import `package:geobase/geobase.dart`

There are also partial packages containing only a certain subset. See the Packages section below.

See also the geodata package that extends capabilities of geobase by providing geospatial API clients to read GeoJSON data sources and OGC API Features web services.

🚀 Hint: The Geospatial demos for Dart repository contains sample code showing also how to use this package!

Coordinates

Geographic coordinates

Geographic coordinates are based on a spherical or ellipsoidal coordinate system representing positions on the Earth as longitude (lon) and latitude (lat).

Elevation (elev) in meters and measure (m) coordinates are optional.

Geographic positions:

  // A geographic position with longitude and latitude.
  Geographic(lon: -0.0014, lat: 51.4778);

  // A geographic position with longitude, latitude and elevation.
  Geographic(lon: -0.0014, lat: 51.4778, elev: 45.0);

  // A geographic position with longitude, latitude, elevation and measure.
  Geographic(lon: -0.0014, lat: 51.4778, elev: 45.0, m: 123.0);

  // The last sample also from a double list or text (order: lon, lat, elev, m).
  Geographic.build([-0.0014, 51.4778, 45.0, 123.0]);
  Geographic.parse('-0.0014,51.4778,45.0,123.0');
  Geographic.parse('-0.0014 51.4778 45.0 123.0', delimiter: ' ');

Geographic bounding boxes:

  // A geographic bbox (-20 .. 20 in longitude, 50 .. 60 in latitude).
  GeoBox(west: -20, south: 50, east: 20, north: 60);

  // A geographic bbox with limits (100 .. 200) on the elevation coordinate too.
  GeoBox(west: -20, south: 50, minElev: 100, east: 20, north: 60, maxElev: 200);

  // The last sample also from a double list or text.
  GeoBox.build([-20, 50, 100, 20, 60, 200]);
  GeoBox.parse('-20,50,100,20,60,200');

Projected coordinates

Projected coordinates represent projected or cartesian (XYZ) coordinates with an optional measure (m) coordinate. For projected map positions x often represents easting (E) and y represents northing (N), however a coordinate reference system might specify something else too.

The m (measure) coordinate represents a measurement or a value on a linear referencing system (like time). It could be associated with a 2D position (x, y, m) or a 3D position (x, y, z, m).

Projected positions:

  // A projected position with x and y.
  Projected(x: 708221.0, y: 5707225.0);

  // A projected position with x, y and z.
  Projected(x: 708221.0, y: 5707225.0, z: 45.0);

  // A projected position with x, y, z and m.
  Projected(x: 708221.0, y: 5707225.0, z: 45.0, m: 123.0);

  // The last sample also from a double list or text (order: x, y, z, m).
  Projected.build([708221.0, 5707225.0, 45.0, 123.0]);
  Projected.parse('708221.0,5707225.0,45.0,123.0');
  Projected.parse('708221.0 5707225.0 45.0 123.0', delimiter: ' ');

Projected bounding boxes:

  // A projected bbox with limits on x and y.
  ProjBox(minX: 10, minY: 10, maxX: 20, maxY: 20);

  // A projected bbox with limits on x, y and z.
  ProjBox(minX: 10, minY: 10, minZ: 10, maxX: 20, maxY: 20, maxZ: 20);

  // The last sample also from a double list or text.
  ProjBox.build([10, 10, 10, 20, 20, 20]);
  ProjBox.parse('10,10,10,20,20,20');

Scalable coordinates

Scalable coordinates are projected coordinates associated with a level of detail (LOD) or a zoom level. They are used for example by tiling schemes to represent pixels or tiles in tile matrices.

The Scalable2i class represents projected x, y coordinates at zoom level, with all values as integers.

  // A pixel with a zoom level (or LOD = level of detail) coordinates.
  const pixel = Scalable2i(zoom: 9, x: 23, y: 10);

  // Such coordinates can be scaled to other zoom levels.
  pixel.zoomIn(); // => Scalable2i(zoom: 10, x: 46, y: 20);
  pixel.zoomOut(); // => Scalable2i(zoom: 8, x: 11, y: 5);
  pixel.zoomTo(13); // => Scalable2i(zoom: 13, x: 368, y: 160));

Summary

The summary of projected, geographic and scalable coordinate values in the basic position classes:

Class	Required coordinates	Optional coordinates
Projected	x, y	z, m
Geographic	lon, lat	elev, m
Scalable2i	zoom, x, y

The summary of basic bounding box classes:

Class	Required coordinates	Optional coordinates
ProjBox	minX, minY, maxX, maxY	minZ, minM, maxZ, maxM
GeoBox	west, south, east, north	minElev, minM, maxElev, maxM

In some interfaces, for example for positions, coordinate values are referenced only by x, y, z and m property names. So in such a case and in the context of this package, for geographic coordinates x represents longitude, y represents latitude, and z represents elevation (or height or altitude).

The Position interface is a super type for Projected and Geographic, and the Box interface is a super type for ProjBox and GeoBox. Please see more information about them in the API reference.

Coordinate arrays

Position and bounding box classes introduced in the previous section are used when handling positions or bounding boxes (bounds) individually.

However to handle coordinate data in geometry objects and geospatial data formats also, efficient array data structures for coordinate values (as double numeric values) are needed:

Class	Description
PositionArray	Coordinate values of 0 to N positions as a flat structure.
PositionCoords	Coordinate values of a single position.
BoxCoords	Coordinate values of a single bounding box.

All these classes implement Iterable<double> allowing instances of them to be used in places requiring the Iterable<double> type. At the same time, for example PositionCoords is also a valid Position and BoxCoords is a valid Box.

There are also specialized sub classes of PositionCoords for projected coordinates (enabling more compact code when creating instances):

Class	2D/3D	Coords	Values	x	y	z	m
XY	2D	2	double	+	+
XYZ	3D	3	double	+	+	+
XYM	2D	3	double	+	+		+
XYZM	3D	4	double	+	+	+	+

And similar classes for geographic coordinates:

Class	2D/3D	Coords	Values	lon (x)	lat (y)	elev (z)	m
LonLat	2D	2	double	+	+
LonLatElev	3D	3	double	+	+	+
LonLatM	2D	3	double	+	+		+
LonLatElevM	3D	4	double	+	+	+	+

As described above, PositionArray represents coordinate values of 0 to N positions as a flat structure. That is, there is no array of positions with each having an array of coordinate values, but a single flat array of coordinate values (double). This is best illustrated by code samples below:

  // A position array with three positions each with x and y coordinates.
  PositionArray.view(
    [
      10.0, 11.0, // (x, y) for position 0
      20.0, 21.0, // (x, y) for position 1
      30.0, 31.0, // (x, y) for position 2
    ],
    type: Coords.xy,
  );

  // A position array with three positions each with x, y and z coordinates.
  PositionArray.view(
    [
      10.0, 11.0, 12.0, // (x, y, z) for position 0
      20.0, 21.0, 22.0, // (x, y, z) for position 1
      30.0, 31.0, 32.0, // (x, y, z) for position 2
    ],
    type: Coords.xyz,
  );

The coordinate type (using a Coords enum value) must be defined when creating position arrays. Expected coordinate values (exactly in this order) for each type are described below:

Type	Projected values	Geographic values
Coords.xy	x, y	lon, lat
Coords.xyz	x, y, z	lon, lat, elev
Coords.xym	x, y, m	lon, lat, m
Coords.xyzm	x, y, z, m	lon, lat, elev, m

Geometries

Geometry types

Geometry primitive types supported by this package (with samples adapted from the samples of the Wikipedia page about WKT, and compatible also with GeoJSON):

Geometry	Shape	Dart code to build objects
Point		Point(XY(30.0, 10.0)) Point.build([30.0, 10.0])
LineString		LineString.build([30, 10, 10, 30, 40, 40], type: Coords.xy)
Polygon		Polygon.build([[30, 10, 40, 40, 20, 40, 10, 20, 30, 10]], type: Coords.xy)
Polygon (with a hole)		Polygon.build([[35, 10, 45, 45, 15, 40, 10, 20, 35, 10], [20, 30, 35, 35, 30, 20, 20, 30]], type: Coords.xy)

Also multipart geometry classes are supported:

Geometry	Shape	Dart code to build objects
MultiPoint		MultiPoint.build([[10, 40], [40, 30], [20, 20], [30, 10]], type: Coords.xy)
MultiLineString		MultiLineString.build([[10, 10, 20, 20, 10, 40], [40, 40, 30, 30, 40, 20, 30, 10]], type: Coords.xy)
MultiPolygon		MultiPolygon.build([[[30, 20, 45, 40, 10, 40, 30, 20]], [[15, 5, 40, 10, 10, 20, 5, 10, 15, 5]]], type: Coords.xy)
MultiPolygon (with a hole)		MultiPolygon.build([[[40, 40, 20, 45, 45, 30, 40, 40]], [[20, 35, 10, 30, 10, 10, 30, 5, 45, 20, 20, 35], [30, 20, 20, 15, 20, 25, 30, 20]]], type: Coords.xy)
GeometryCollection		GeometryCollection([Point(XY(40, 10)), LineString.build([10, 10, 20, 20, 10, 40], type: Coords.xy), Polygon.build([[40, 40, 20, 45, 45, 30, 40, 40]], type: Coords.xy)])

Geospatial features

Feature objects

According to the OGC Glossary a geospatial feature is a digital representation of a real world entity. It has a spatial domain, a temporal domain, or a spatial/temporal domain as one of its attributes. Examples of features include almost anything that can be placed in time and space, including desks, buildings, cities, trees, forest stands, ecosystems, delivery vehicles, snow removal routes, oil wells, oil pipelines, oil spill, and so on.

Below is an illustration of features in a simple vector map. Wells are features with point geometries, rivers with line strings (or polyline) geometries, and finally lakes are features with polygon geometries. Features normally contain also an identifier and other attributes (or properties) along with a geometry.

Sets of features are contained by feature collections.

As specified also by the GeoJSON format a Feature object contains a geometry object and additional members (like "id" and "properties"). A FeatureCollection object contains an array of Feature objects. Both may also contain "bbox" or bounding box. Any other members on Feature and FeatureCollection objects are foreign members, allowed property values or geometry objects, but not specified by the GeoJSON model (and so potentially not known by many GeoJSON parsers).

This package models features and feature collections according to these definitions.

Feature

A single Feature object:

  // A geospatial feature with id, a point geometry and properties.
  Feature(
    id: 'ROG',
    // a point geometry with a position (lon, lat, elev)
    geometry: Point.build([-0.0014, 51.4778, 45.0]),
    properties: {
      'title': 'Royal Observatory',
      'place': 'Greenwich',
      'city': 'London',
      'isMuseum': true,
      'measure': 5.79,
    },
  );

Naturally, the geometry member could also contain any other geometry types described earlier, not just points.

An optional id, when given, should be either a string or an integer. The properties member defines feature properties as a map with the JSON Object compatible model (or Map<String, dynamic> as such data is typed in Dart).

FeatureCollection

A FeatureCollection object with Feature objects:

  // A geospatial feature collection (with two features):
  FeatureCollection([
    Feature(
      id: 'ROG',
      geometry: Point(LonLatElev(-0.0014, 51.4778, 45.0)),
      properties: {
        'title': 'Royal Observatory',
        'place': 'Greenwich',
        'city': 'London',
        'isMuseum': true,
        'measure': 5.79,
      },
    ),
    Feature(
      id: 'TB',
      geometry: Point(LonLat(-0.075406, 51.5055)),
      properties: {
        'title': 'Tower Bridge',
        'city': 'London',
        'built': 1886,
      },
    ),
  ]);

Vector data formats

GeoJSON

As already described GeoJSON is a format for encoding geometry, feature and feature collection objects. The data structures introduced on previous geometries and geospatial features sections are modelled to support encoding and decoding GeoJSON data.

As specified by the RFC 7946 standard, all GeoJSON geometry objects use WGS 84 geographic coordinates. Also alternative coordinate reference systems can be used when involved parties have a prior arrangement of using other systems.

This package supports encoding GeoJSON text from geometry and feature objects:

  // build a LineString sample geometry
  final lineString = LineString.build(
    [-1.1, -1.1, 2.1, -2.5, 3.5, -3.49],
    type: Coords.xy,
    bounds: [-1.1, -3.49, 3.5, -1.1],
  );

  // ... and print it as GeoJSON text:
  //   { 
  //     "type":"LineString",
  //     "bbox":[-1.1,-3.49,3.5,-1.1],
  //     "coordinates":[[-1.1,-1.1],[2.1,-2.5],[3.5,-3.49]]
  //   }
  print(lineString.toText(format: GeoJSON.geometry));

  // GeoJSON representation for other geometries, features and feature
  // collections can be produced with `toText` methdod also.

  // here a Feature is printed as GeoJSON text (with 3 decimals on doubles):
  //   {
  //     "type":"Feature",
  //     "id":"TB",
  //     "geometry":{"type":"Point","coordinates":[-0.075,51.505]},
  //     "properties":{"title":"Tower Bridge","city":"London","built":1886}
  //   }
  final feature = Feature(
    id: 'TB',
    geometry: Point(LonLat(-0.075406, 51.5055)),
    properties: {
      'title': 'Tower Bridge',
      'city': 'London',
      'built': 1886,
    },
  );
  print(feature.toText(format: GeoJSON.feature, decimals: 3));

Geometry and feature objects can be also parsed from their GeoJSON text representations:

  // sample GeoJSON text representation (a feature collection with two features)
  const sample = '''
    {
      "type": "FeatureCollection",
      "features": [
        {
          "type": "Feature",
          "id": "ROG",
          "geometry": {
            "type": "Point",
            "coordinates": [-0.0014, 51.4778, 45.0]  
          },
          "properties": {
            "title": "Royal Observatory",
            "place": "Greenwich"
          }
        }, 
        {
          "type": "Feature",
          "id": "TB",
          "geometry": {
            "type": "Point",
            "coordinates": [-0.075406, 51.5055]  
          },
          "properties": {
            "title": "Tower Bridge",
            "built": 1886
          }
        } 
      ]
    }
  ''';

  // parse a FeatureCollection object using the decoder of the GeoJSON format
  final collection = FeatureCollection.parse(sample, format: GeoJSON.feature);

  // loop through features and print id, geometry and properties for each
  for (final feature in collection.features) {
    print('Feature with id: ${feature.id}');
    print('  geometry: ${feature.geometry}');
    print('  properties:');
    for (final key in feature.properties.keys) {
      print('    $key: ${feature.properties[key]}');
    }
  }

All geometry, feature and feature collection classes has similar parse methods to support parsing from GeoJSON.

WKT

Well-known text representation of geometry (WKT) is a text markup language for representing vector geometry objects. It's specified by the Simple Feature Access - Part 1: Common Architecture standard.

Positions and geometries can be encoded to WKT text representations. However feature and feature collections cannot be written to WKT even if those are supported by GeoJSON.

A sample to encode a Point geometry to WKT (with z and m coordinates too):

  // create a Point geometry
  final point = Point.build([10.123, 20.25, -30.95, -1.999], type: Coords.xyzm);

  // format it as WKT text that is printed:
  //    POINT ZM(10.123 20.25 -30.95 -1.999)
  print(point.toText(format: WKT.geometry));

It's possible to encode geometry data as WKT text also without creating geometry objects first. However this requires accessing an encoder instance from the WKT format, and then writing content to that encoder. See sample below:

  // geometry text format encoder for WKT
  const format = WKT.geometry;
  final encoder = format.encoder();

  // prints:
  //    POINT ZM(10.123 20.25 -30.95 -1.999)
  encoder.writer.point(
    [10.123, 20.25, -30.95, -1.999],
    type: Coords.xyzm,
  );
  print(encoder.toText());

Such format encoders (and formatting without geometry objects) are suppported also for GeoJSON. However for both WKT and GeoJSON encoding might be easier using concrete geometry model objects.

Currently this package does not (yet) support parsing from WKT text.

WKB

The WKB class provides encoders and decoders for Well-known binary binary format supporting simple geometry objects.

Two different approaches to use WKB encoders and decoders are presented in this section.

First a not-so-simple sample below processes data for demo purposes in following steps:

1. write geometry content as a source
2. encode content as WKB bytes
3. decode those WKB bytes
4. WKT encoder receives input from WKB decoder, and prints WKT text

  // geometry binary format encoder for WKB
  const format = WKB.geometry;
  final encoder = format.encoder();

  // write geometries (here only point) to content writer of the encoder
  encoder.writer.point(
    [10.123, 20.25, -30.95, -1.999],
    type: Coords.xyzm,
  );

  // get encoded bytes (Uint8List) and Base64 encoded text (String)
  final wkbBytes = encoder.toBytes();
  final wkbBytesAsBase64 = encoder.toText();

  // prints (point encoded to WKB binary data, formatted as Base64 text):
  //    AAAAC7lAJD752yLQ5UA0QAAAAAAAwD7zMzMzMzO///vnbItDlg==
  print(wkbBytesAsBase64);

  // next decode this WKB binary data and use WKT text format encoder as target

  // geometry text format encoder for WKT
  final wktEncoder = WKT.geometry.encoder();

  // geometry binary format decoder for WKB
  // (with content writer of the WKT encoder set as a target for decoding)
  final decoder = WKB.geometry.decoder(wktEncoder.writer);

  // now decode those WKB bytes (Uint8List) created already at the start
  decoder.decodeBytes(wkbBytes);

  // finally print WKT text:
  //    POINT ZM(10.123 20.25 -30.95 -1.999)
  print(wktEncoder.toText());

The solution above can be simplified a lot by using geometry model objects:

  // create a Point object
  final point = Point(XYZM(10.123, 20.25, -30.95, -1.999));

  // get encoded bytes (Uint8List)
  final wkbBytes = point.toBytes(format: WKB.geometry);

  // at this point our WKB bytes could be sent to another system...

  // then create a Point object, but now decoding it from WKB bytes
  final pointDecoded = Point.decode(wkbBytes, format: WKB.geometry);

  // finally print WKT text:
  //    POINT ZM(10.123 20.25 -30.95 -1.999)
  print(pointDecoded.toText(format: WKT.geometry));

This second solution uses same formats, encoders, decoders and builders as the first one, but the details of using them is hidden under an easier interface.

As a small bonus let's continue the last sample a bit:

  // or as a bonus of this solution it's as easy to print it as GeoJSON text too
  //    {"type":"Point","coordinates":[10.123,20.25,-30.95,-1.999]}
  print(pointDecoded.toText(format: GeoJSON.geometry));

  // great, but, we just forgot that GeoJSON should not contain m coordinates...
  //    {"type":"Point","coordinates":[10.123,20.25,-30.95]}
  print(
    pointDecoded.toText(
      format: GeoJSON.geometryFormat(conf: GeoJsonConf(ignoreMeasured: true)),
    ),
  );

Meta

Temporal data

Temporal data can be represented as instants (a time stamp) and intervals (an open or a closed interval between time stamps).

  // Instants can be created from `DateTime` or parsed from text.
  Instant(DateTime.utc(2020, 10, 31, 09, 30));
  Instant.parse('2020-10-31 09:30Z');

  // Intervals (open-started, open-ended, closed).
  Interval.openStart(DateTime.utc(2020, 10, 31));
  Interval.openEnd(DateTime.utc(2020, 10, 01));
  Interval.closed(DateTime.utc(2020, 10, 01), DateTime.utc(2020, 10, 31));

  // Same intervals parsed (by the "start/end" format, ".." for open limits).
  Interval.parse('../2020-10-31');
  Interval.parse('2020-10-01/..');
  Interval.parse('2020-10-01/2020-10-31');

Geospatial extents

Extent objects have both spatial bounds and temporal interval, and they are useful in metadata structures for geospatial data sources.

  // An extent with spatial (WGS 84 longitude-latitude) and temporal parts.
  GeoExtent.single(
    crs: 'EPSG:4326',
    bbox: GeoBox(west: -20.0, south: 50.0, east: 20.0, north: 60.0),
    interval: Interval.parse('../2020-10-31'),
  );

  // An extent with multiple spatial bounds and temporal interval segments.
  GeoExtent.multi(
    crs: 'EPSG:4326',
    boxes: [
      GeoBox(west: -20.0, south: 50.0, east: 20.0, north: 60.0),
      GeoBox(west: 40.0, south: 50.0, east: 60.0, north: 60.0),
    ],
    intervals: [
      Interval.parse('2020-10-01/2020-10-05'),
      Interval.parse('2020-10-27/2020-10-31'),
    ],
  );

The crs property in extents above refer to a Coordinate reference system that is a coordinate-based local, regional or global system used to locate geographical entities.

This package does not define any crs constants, please refer to registries like The EPSG dataset.

Projections

WGS 84 to Web Mercator

Built-in coordinate projections (currently only between WGS84 and Web Mercator).

Here projected coordinates are metric coordinates with both x and y values having the valid value range of (-20037508.34, 20037508.34).

  // Built-in coordinate projections (currently only between WGS 84 and
  // Web Mercator)

  // Geographic (WGS 84 longitude-latitude) to Projected (WGS 84 Web Mercator)
  final forward = WGS84.webMercator.forward;
  final projected = forward.project(
    const Geographic(lon: -0.0014, lat: 51.4778),
    to: Projected.create,
  );

  // Projected (WGS 84 Web Mercator) to Geographic (WGS 84 longitude-latitude)
  final inverse = WGS84.webMercator.inverse;
  final unprojected = inverse.project(
    projected,
    to: Geographic.create,
  );

  print('$unprojected <=> $projected');

With proj4dart

Coordinate projections based on the external proj4dart package requires imports like:

// import the default geobase library
import 'package:geobase/geobase.dart';

// need also an additional import with dependency to `proj4dart` 
import 'package:geobase/projections_proj4d.dart';

Then a sample to use coordinate projections:

  // A projection adapter from WGS84 (EPSG:4326) to EPSG:23700 (with definition)
  // (based on the sample at https://pub.dev/packages/proj4dart).
  final adapter = Proj4d.resolve(
    'EPSG:4326',
    'EPSG:23700',
    toDef: '+proj=somerc +lat_0=47.14439372222222 +lon_0=19.04857177777778 '
        '+k_0=0.99993 +x_0=650000 +y_0=200000 +ellps=GRS67 '
        '+towgs84=52.17,-71.82,-14.9,0,0,0,0 +units=m +no_defs',
  );

  // Apply a forward projection to EPSG:23700.
  print(
    adapter.forward.project(
      const Geographic(lon: 17.8880, lat: 46.8922),
      to: Projected.create,
    ),
  );

Please see the documentation of proj4dart package about it's capabilities, and accuracy of forward and inverse projections.

Tiling schemes

Web Mercator Quad

WebMercatorQuad is a "Google Maps Compatible" tile matrix set with tiles defined in the WGS 84 / Web Mercator projection ("EPSG:3857").

Using WebMercatorQuad involves following coordinates:

• position: geographic coordinates (longitude, latitude)
• world: a position projected to the pixel space of the map at level 0
• pixel: pixel coordinates (x, y) in the pixel space of the map at zoom
• tile: tile coordinates (x, y) in the tile matrix at zoom

OGC Two Dimensional Tile Matrix Set specifies:

Level 0 allows representing most of the world (limited to latitudes between approximately ±85 degrees) in a single tile of 256x256 pixels (Mercator projection cannot cover the whole world because mathematically the poles are at infinity). The next level represents most of the world in 2x2 tiles of 256x256 pixels and so on in powers of 2. Mercator projection distorts the pixel size closer to the poles. The pixel sizes provided here are only valid next to the equator.

See below how to calcalate between geographic positions, world coordinates, pixel coordinates and tile coordinates:

  // "WebMercatorQuad" tile matrix set with 256 x 256 pixel tiles and with
  // "top-left" origin for the tile matrix and map pixel space
  const quad = WebMercatorQuad.epsg3857();

  // source position as geographic coordinates
  const position = Geographic(lon: -0.0014, lat: 51.4778);

  // get world, tile and pixel coordinates for a geographic position
  print(quad.positionToWorld(position)); // ~ x=127.999004 y=85.160341
  print(quad.positionToTile(position, zoom: 2)); // zoom=2 x=1 y=1
  print(quad.positionToPixel(position, zoom: 2)); // zoom=2 x=511 y=340
  print(quad.positionToPixel(position, zoom: 4)); // zoom=4 x=2047 y=1362

  // world coordinates can be instantiated as projected coordinates
  // x range: (0.0, 256.0) / y range: (0.0, 256.0)
  const world = Projected(x: 127.99900444444444, y: 85.16034098329446);

  // from world coordinates to tile and pixel coordinates
  print(quad.worldToTile(world, zoom: 2)); // zoom=2 x=1 y=1
  print(quad.worldToPixel(world, zoom: 2)); // zoom=2 x=511 y=340
  print(quad.worldToPixel(world, zoom: 4)); // zoom=4 x=2047 y=1362

  // tile and pixel coordinates with integer values can be defined too
  const tile = Scalable2i(zoom: 2, x: 1, y: 1);
  const pixel = Scalable2i(zoom: 2, x: 511, y: 340);

  // tile and pixel coordinates can be zoomed (scaled to other level of details)
  print(pixel.zoomIn()); // zoom=3 x=1022 y=680
  print(pixel.zoomOut()); // zoom=1 x=255 y=170

  // get tile bounds and pixel position (accucy lost) as geographic coordinates
  print(quad.tileToBounds(tile)); // west: -90 south: 0 east: 0 north: 66.51326
  print(quad.pixelToPosition(pixel)); // longitude: -0.17578 latitude: 51.50874

  // world coordinates returns geographic positions still accurately
  print(quad.worldToPosition(world)); // longitude: -0.00140 latitude: 51.47780

  // a quad key is a string identifier for tiles
  print(quad.tileToQuadKey(tile)); // "03"
  print(quad.quadKeyToTile('03')); // zoom=2 x=1 y=1
  print(quad.quadKeyToTile('0321')); // zoom=4 x=5 y=6

  // tile size and map bounds can be checked dynamically
  print(quad.tileSize); // 256
  print(quad.mapBounds()); // ~ west: -180 south: -85.05 east: 180 north: 85.05

  // matrix width and height tells number of tiles in a given zoom level
  print('${quad.matrixWidth(2)} x ${quad.matrixHeight(2)}'); // 4 x 4
  print('${quad.matrixWidth(10)} x ${quad.matrixHeight(10)}'); // 1024 x 1024

  // map width and height tells number of pixels in a given zoom level
  print('${quad.mapWidth(2)} x ${quad.mapHeight(2)}'); // 1024 x 1024
  print('${quad.mapWidth(10)} x ${quad.mapHeight(10)}'); // 262144 x 262144

  // ground resolutions and scale denominator for zoom level 10 at the Equator
  print(quad.tileGroundResolution(10)); // ~ 39135.76 (meters)
  print(quad.pixelGroundResolution(10)); // ~ 152.87 (meters)
  print(quad.scaleDenominator(10)); // ~ 545978.77

  // ground resolutions and scale denominator for zoom level 10 at lat 51.4778
  print(quad.pixelGroundResolutionAt(latitude: 51.4778, zoom: 10)); // ~ 95.21
  print(quad.scaleDenominatorAt(latitude: 51.4778, zoom: 10)); // ~ 340045.31

Global Geodetic Quad

GlobalGeodeticQuad (or "World CRS84 Quad" for WGS 84) is a tile matrix set with tiles defined in the Equirectangular Plate Carrée projection.

At the zoom level 0 the world is covered by two tiles (tile matrix width is 2 and matrix height is 1). The western tile (x=0, y=0) is for the negative longitudes and the eastern tile (x=1, y=0) for the positive longitudes.

  // "World CRS 84" tile matrix set with 256 x 256 pixel tiles and with
  // "top-left" origin for the tile matrix and map pixel space
  const quad = GlobalGeodeticQuad.worldCrs84();

  // source position as geographic coordinates
  const position = Geographic(lon: -0.0014, lat: 51.4778);

  // get world, tile and pixel coordinates for a geographic position
  print(quad.positionToWorld(position)); // ~ x=255.998009 y=54.787129
  print(quad.positionToTile(position, zoom: 2)); // zoom=2 x=3 y=0
  print(quad.positionToPixel(position, zoom: 2)); // zoom=2 x=1023 y=219
  print(quad.positionToPixel(position, zoom: 4)); // zoom=4 x=4095 y=876

  // world coordinates can be instantiated as projected coordinates
  // x range: (0.0, 512.0) / y range: (0.0, 256.0)
  const world = Projected(x: 255.99800888888888, y: 54.78712888888889);

  // from world coordinates to tile and pixel coordinates
  print(quad.worldToTile(world, zoom: 2)); // zoom=2 x=3 y=0
  print(quad.worldToPixel(world, zoom: 2)); // zoom=2 x=1023 y=219
  print(quad.worldToPixel(world, zoom: 4)); //  zoom=4 x=4095 y=876

  // tile and pixel coordinates with integer values can be defined too
  const tile = Scalable2i(zoom: 2, x: 3, y: 0);
  const pixel = Scalable2i(zoom: 2, x: 1023, y: 219);

  // get tile bounds and pixel position (accucy lost) as geographic coordinates
  print(quad.tileToBounds(tile)); // west: -45 south: 45 east: 0 north: 90
  print(quad.pixelToPosition(pixel)); // longitude: -0.08789 latitude: 51.41602

  // world coordinates returns geographic positions still accurately
  print(quad.worldToPosition(world)); // longitude: -0.00140 latitude: 51.4778

  // tile size and map bounds can be checked dynamically
  print(quad.tileSize); // 256
  print(quad.mapBounds()); // west: -180 south: -90 east: 180 north: 90

  // matrix width and height tells number of tiles in a given zoom level
  print('${quad.matrixWidth(2)} x ${quad.matrixHeight(2)}'); // 8 x 4
  print('${quad.matrixWidth(10)} x ${quad.matrixHeight(10)}'); // 2048 x 1024

  // map width and height tells number of pixels in a given zoom level
  print('${quad.mapWidth(2)} x ${quad.mapHeight(2)}'); // 2048 x 1024
  print('${quad.mapWidth(10)} x ${quad.mapHeight(10)}'); // 524288 x 262144

  // arc resolutions and scale denominator for zoom level 10 at the Equator
  print(quad.tileArcResolution(10)); // ~ 0.175781 (° degrees)
  print(quad.pixelArcResolution(10)); // ~ 0.000686646 (° degrees)
  print(quad.scaleDenominator(10)); // ~ 272989.39

Reference

Packages

The geobase library contains also following partial packages, that can be used to import only a certain subset instead of the whole geobase package:

Package	Description
codes	Enums (codes) for geospatial coordinate, geometry types and canvas origin.
constants	Geodetic and screen related constants.
coordinates	Geographic (longitude-latitude) and projected positions and bounding boxes.
meta	Temporal data structures (instant, interval) and spatial extents.
projections	Geospatial projections (currently only between WGS84 and Web Mercator).
projections_proj4d	Projections provided by the external proj4dart package.
tiling	Tiling schemes and tile matrix sets (web mercator, global geodetic).
vector	Text and binary formats for vector data (features, geometries, coordinates).
vector_data	Data structures for positions, geometries, features and feature collections.

External packages geobase is depending on:

• equatable for equality and hash utils
• meta for annotations
• proj4dart for coordinate projections

Authors

This project is authored by Navibyte.

More information and other links are available at the geospatial repository from GitHub.

License

This project is licensed under the "BSD-3-Clause"-style license.

Please see the LICENSE.