Geometry Input/Output Formats

Spatial data interoperability is crucial in modern GIS workflows. Whether you're importing data from external sources, exporting results for visualization, or integrating with web applications, understanding geometry input/output formats is essential. PostGIS supports a comprehensive range of formats, making it easy to work with spatial data across different platforms and applications.

Why Do Geometry Formats Matter?

Geometry I/O formats allow spatial data to be read, stored, and shared across different systems and applications. Whether you're exporting a dataset to a web application, visualizing data in QGIS, processing data in Python, or sharing results with stakeholders, choosing the right format ensures compatibility and efficiency.

PostGIS supports industry-standard formats that enable seamless integration with virtually any GIS software, web mapping platform, or spatial analysis tool.

Well-Known Text (WKT) - Human-Readable Format

WKT is a text-based format that represents geometries in a human-readable way. It's perfect for debugging, manual data entry, and educational purposes.

Creating and Reading WKT

-- Convert geometry to WKT
SELECT ST_AsText(geom) AS wkt_geometry
FROM landmarks;

-- Create geometry from WKT
SELECT ST_GeomFromText('POINT(77.59 12.97)', 4326) AS point_geom;

-- More complex geometries
SELECT ST_GeomFromText('LINESTRING(77.58 12.96, 77.60 12.98, 77.62 13.00)', 4326);
SELECT ST_GeomFromText('POLYGON((77.58 12.96, 77.60 12.96, 77.60 12.98, 77.58 12.98, 77.58 12.96))', 4326);

WKT Advantages and Use Cases

• Human-readable: Easy to understand and debug
• Manual editing: Can be typed or edited by hand
• Educational: Great for learning spatial concepts
• Copy-paste friendly: Easy to share between tools
• SQL-friendly: Works well in database queries

Well-Known Binary (WKB) - Compact Binary Format

WKB is a binary format that provides compact storage and fast processing. It's ideal for internal storage and network transmission.

-- Convert geometry to WKB (hexadecimal representation)
SELECT ST_AsBinary(geom) AS wkb_geometry,
       encode(ST_AsBinary(geom), 'hex') AS wkb_hex
FROM landmarks;

-- Create geometry from WKB
SELECT ST_GeomFromWKB('\x0101000020E6100000000000000000F03F0000000000000040');

-- Using hex-encoded WKB
SELECT ST_GeomFromWKB(decode('0101000020E6100000000000000000F03F0000000000000040', 'hex'));

GeoJSON - Web-Friendly Format

GeoJSON is a JSON-based format that's become the standard for web mapping applications and APIs.

-- Convert geometry to GeoJSON
SELECT ST_AsGeoJSON(geom) AS geojson_geometry
FROM landmarks;

-- Create geometry from GeoJSON
SELECT ST_GeomFromGeoJSON('{"type":"Point","coordinates":[77.59,12.97]}');

-- GeoJSON with properties (using row_to_json)
SELECT json_build_object(
  'type', 'Feature',
  'geometry', ST_AsGeoJSON(geom)::json,
  'properties', json_build_object(
    'name', name,
    'type', landmark_type
  )
) AS feature_geojson
FROM landmarks;

-- Complete FeatureCollection
SELECT json_build_object(
  'type', 'FeatureCollection',
  'features', json_agg(
    json_build_object(
      'type', 'Feature',
      'geometry', ST_AsGeoJSON(geom)::json,
      'properties', json_build_object('name', name)
    )
  )
) AS feature_collection
FROM landmarks;

GeoJSON Structure Examples

GeoJSON Use Cases

• Web mapping: Leaflet, Mapbox, OpenLayers
• APIs: REST services and microservices
• JavaScript applications: Frontend mapping applications
• Data exchange: Between web services
• Visualization: D3.js and other visualization libraries

GML - Geography Markup Language

GML is an XML-based format used in OGC standards and enterprise systems.

-- Convert geometry to GML
SELECT ST_AsGML(geom) AS gml_geometry
FROM landmarks;

-- Create geometry from GML
SELECT ST_GeomFromGML('<gml:Point><gml:coordinates>77.59,12.97</gml:coordinates></gml:Point>');

-- GML with different versions
SELECT ST_AsGML(2, geom) AS gml_v2,
       ST_AsGML(3, geom) AS gml_v3
FROM landmarks;

GML Characteristics

KML - Keyhole Markup Language

KML is designed for visualization in Google Earth and similar platforms.

-- Convert geometry to KML
SELECT ST_AsKML(geom) AS kml_geometry
FROM landmarks;

-- Create geometry from KML
SELECT ST_GeomFromKML('<Point><coordinates>77.59,12.97</coordinates></Point>');

-- KML with styling and descriptions
SELECT ST_AsKML(geom, 15) AS detailed_kml  -- 15 decimal places
FROM landmarks;

KML Applications

• Google Earth: Primary visualization platform
• Presentations: Visual overlays for reports
• Public engagement: Sharing spatial data with non-GIS users
• Mobile apps: Location-based applications

Format Conversion and Validation

Converting Between Formats

-- Chain conversions
SELECT ST_AsGeoJSON(ST_GeomFromText('POINT(77.59 12.97)', 4326)) AS wkt_to_geojson;

-- Convert WKB to GML
SELECT ST_AsGML(ST_GeomFromWKB(decode('0101000020E6100000000000000000F03F0000000000000040','hex')));

-- Batch conversion example
SELECT 
  name,
  ST_AsText(geom) AS wkt,
  ST_AsGeoJSON(geom) AS geojson,
  ST_AsKML(geom) AS kml
FROM landmarks;

Format Validation

-- Validate geometries before conversion
SELECT 
  name,
  ST_IsValid(geom) AS is_valid,
  ST_IsValidReason(geom) AS validation_reason
FROM landmarks;

-- Fix invalid geometries
UPDATE landmarks 
SET geom = ST_MakeValid(geom) 
WHERE NOT ST_IsValid(geom);

-- Validate specific format inputs
SELECT ST_IsValid(ST_GeomFromGeoJSON('{"type":"Point","coordinates":[77.59,12.97]}'));

Performance Considerations

Real-World Integration Examples

Web API Integration

-- Create REST API endpoint response
CREATE OR REPLACE FUNCTION get_landmarks_geojson()
RETURNS json AS $$
BEGIN
  RETURN (
    SELECT json_build_object(
      'type', 'FeatureCollection',
      'features', json_agg(
        json_build_object(
          'type', 'Feature',
          'geometry', ST_AsGeoJSON(geom)::json,
          'properties', json_build_object(
            'id', id,
            'name', name,
            'category', category
          )
        )
      )
    )
    FROM landmarks
  );
END;
$$ LANGUAGE plpgsql;

Data Import Pipeline

-- Import from various formats
CREATE TABLE imported_data (
  id SERIAL PRIMARY KEY,
  source_format TEXT,
  geom GEOMETRY,
  properties JSONB
);

-- Insert from different sources
INSERT INTO imported_data (source_format, geom, properties)
VALUES 
  ('WKT', ST_GeomFromText('POINT(77.59 12.97)', 4326), '{"name": "Location A"}'),
  ('GeoJSON', ST_GeomFromGeoJSON('{"type":"Point","coordinates":[77.60,12.98]}'), '{"name": "Location B"}'),
  ('KML', ST_GeomFromKML('77.61,12.99'), '{"name": "Location C"}');

Best Practices

1. Choose the right format for your use case:
   • WKB for internal storage and performance
   • GeoJSON for web applications
   • WKT for debugging and manual editing
   • KML for visualization and public sharing
2. Always validate input data: Use ST_IsValid() before processing
3. Handle coordinate precision: Consider decimal places for your application
4. Include SRID information: Always specify coordinate reference systems
5. Optimize for your workflow: Cache converted formats if used repeatedly
6. Consider file size: Choose compact formats for large datasets

Format Selection Guide