Spatial Database Types of Spatial Data

Spatial Database Types of Spatial Data

^Ø Point Data

Points in a multidimensional space

E.g., Raster data such as satellite imagery, where each pixel stores a measured value

E.g., Feature vectors extracted from text

^Ø Region Data

Objects have spatial extent with location and boundary.

DB typically uses geometric approximations constructed using line segments, polygons, etc., called vector data.

Types of Spatial Queries

^Ø Spatial Range Queries

Find all cities within 50 miles of Madison Query has associated region (location, boundary)

Answer includes ovelapping or contained data regions

 ^Ø Nearest-Neighbor Queries

Find the 10 cities nearest to Madison Results must be ordered by proximity

^Ø Spatial Join Queries

Find all cities near a lake

Expensive, join condition involves regions and proximity

Applications of Spatial Data

^Ø Geographic Information Systems (GIS)

E.g., ESRI‘s ArcInfo; OpenGIS Consortium

Geospatial information

All classes of spatial queries and data are common

^Ø Computer-Aided Design/Manufacturing

Store spatial objects such as surface of airplane fuselage Range queries and spatial join queries are common

 ^Ø Multimedia Databases

Images, video, text, etc. stored and retrieved by content First converted to feature vector form; high dimensionality Nearest-neighbor queries are the most common

Single-Dimensional Indexes

B+ trees are fundamentally single-dimensional indexes.

When we create a composite search key B+ tree, e.g., an index on <age, sal>, we effectively linearize the 2-dimensional space since we sort entries first by age and then by sal.

Consider entries: <11, 80>, <12, 10> <12, 20>, <13, 75>