Detailed Guide to Vector Data Formats in GIS

What is Vector Data?

Vector data represents real-world features using geometric shapes:

• Points (e.g., landmarks, GPS coordinates)
• Lines (e.g., roads, rivers)
• Polygons (e.g., land parcels, lakes)

Each vector feature also contains attributes (non-spatial data) like names, IDs, or categories.

1. Shapefile (.shp)

Overview:

• Developed by ESRI, Shapefile is one of the oldest and most used GIS vector formats.
• It is a multi-file format, where a single dataset consists of several files:
  • .shp — Geometry data (mandatory)
  • .shx — Shape index (mandatory)
  • .dbf — Attribute data table (mandatory)
  • .prj — Projection information (optional but important)

Strengths:

• Widely supported across almost all GIS platforms.
• Simple and straightforward structure.
• Suitable for small to medium datasets.

Limitations:

• Attribute table (.dbf) limited to 10-character field names.
• Cannot store topology (spatial relationships like adjacency or connectivity).
• Limited support for Unicode text.
• File size limit: 2GB per file.
• No support for storing multiple geometry types (must have separate shapefiles for points, lines, polygons).

Common Use Cases:

• Data exchange between organizations.
• Legacy GIS systems.
• Basic mapping projects.

2. GeoJSON (.geojson)

Overview:

• JSON-based (JavaScript Object Notation) open format designed for web applications.
• Encodes vector geometries (Point, LineString, Polygon, Multi- geometries) in a text-readable format.

Strengths:

• Lightweight and easy to read/edit.
• Excellent for web mapping (e.g., Leaflet, Mapbox).
• Easily parsed by JavaScript-based applications.
• Supports UTF-8 characters (good for multilingual data).

Limitations:

• Not efficient for large datasets (can be slow due to text-based structure).
• Lacks support for advanced GIS functionalities like topologies.
• Coordinate precision can be lost if not handled carefully.

Common Use Cases:

• Web GIS applications and APIs.
• Rapid prototyping of mapping projects.
• Data sharing through web services.

3. KML / KMZ (.kml, .kmz)

Overview:

• Developed by Google, KML (Keyhole Markup Language) is an XML-based format.
• .kmz is a compressed version of KML (zipped).

Strengths:

• Directly used in Google Earth & Google Maps.
• Supports rich symbology, pop-up info bubbles, 3D models, images.
• Very user-friendly for non-GIS audiences.

Limitations:

• Not suitable for spatial analysis or attribute-heavy datasets.
• Limited in handling large datasets or complex geometries.
• Attribute data is less structured compared to shapefiles or GeoJSON.

Common Use Cases:

• Sharing visual geographic data with the public.
• Creating interactive map tours or story maps.
• Simple display of points, paths, and regions.

4. GeoPackage (GPKG)

Overview:

• An OGC (Open Geospatial Consortium) standard.
• Stores vector and raster data in a single SQLite database file.
• Designed as a modern replacement for Shapefiles.

Strengths:

• Single-file storage — easy to manage and share.
• Supports large datasets without performance loss.
• Can store multiple layers (points, lines, polygons) in one file.
• Supports 3D geometries, tiled raster data, and metadata.
• High attribute capacity with no field name restrictions.
• Well-suited for mobile GIS applications.

Limitations:

• Still not universally adopted (some older GIS software may lack full support).
• Slightly more complex structure than flat files (like Shapefile or GeoJSON).

Common Use Cases:

• Enterprise-level GIS projects.
• Mobile GIS apps (e.g., QField, Locus Map).
• Data exchange between modern GIS systems.

Comparison Table

Format	Structure Type	Max File Size	Multiple Layers	Web Friendly	Analysis Capable	Notes
Shapefile	Multi-file	~2 GB	No	No	Yes	Legacy but widely used
GeoJSON	Single text file	N/A	Yes	Yes	Limited	Best for web apps
KML/KMZ	Single file	N/A	Yes	Yes (Google Earth)	Limited	Visual presentations
GeoPackage	Single database	Large	Yes	Partially	Yes	Modern all-in-one forma