computer science

Spatial database

Spatial database is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Spatial database rather than just read about it. In short: A spatial database is a general-purpose database (usually a relational database) that has been enhanced to include spatial data that represents objects defined in a geometric space, along with tools for querying and analyzing such data. Most spatial databases allow the representation of simple geometric objects such as points, lines and polygons.

Key takeaways

Spatial database belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Spatial database to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Spatial database from memory before moving on to harder problems.

Reference excerpt

A spatial database is a general-purpose database (usually a relational database) that has been enhanced to include spatial data that represents objects defined in a geometric space, along with tools for querying and analyzing such data. Most spatial databases allow the representation of simple geometric objects such as points, lines and polygons. Some spatial databases handle more complex structures such as 3D objects, topological coverages, linear networks, and triangulated irregular networks (TINs). While typical databases have developed to manage various numeric and character types of data, such databases require additional functionality to process spatial data types efficiently, and developers have often added geometry or feature data types. Geographic database (or geodatabase) is a georeferenced spatial database, used for storing and manipulating geographic data (or geodata, i.e., data associated with a location on Earth), especially in geographic information systems (GIS). Almost all current relational and object-relational database management systems now have spatial extensions, and some GIS software vendors have developed their own spatial extensions to database management systems. The Open Geospatial Consortium (OGC) developed the Simple Features specification (first released in 1997) and sets standards for adding spatial functionality to database systems. The SQL/MM Spatial ISO/IEC standard is a part of the structured query language and multimedia standard extending the Simple Features.

Characteristics The core functionality added by a spatial extension to a database is one or more spatial datatypes, which allow for the storage of spatial data as attribute values in a table. Most commonly, a single spatial value would be a geometric primitive (point, line, polygon, etc.) based on the vector data model. The datatypes in most spatial databases are based on the OGC Simple Features specification for representing geometric primitives. Some spatial databases also support the storage of raster data. Because all geographic locations must be specified according to a spatial reference system, spatial databases must also allow for the tracking and transformation of coordinate systems. In many systems, when a spatial column is defined in a table, it also includes a choice of coordinate system, chosen from a list of available systems that is stored in a lookup table. The second major functionality extension in a spatial database is the addition of spatial capabilities to the query language (e.g., SQL); these give the spatial database the same query, analysis, and manipulation operations that are available in traditional GIS software. In most relational database management systems, this functionality is implemented as a set of new functions that can be used in SQL SELECT statements. Several types of operations are specified by the Open Geospatial Consortium standard:

Measurement: Computes line length, polygon area, the distance between geometries, etc. Geoprocessing: Modify existing features to create new ones, for example by creating a buffer around them, intersecting features, etc. Predicates: Allows true/false queries about spatial relationships between geometries. Examples include "do two polygons overlap?" or 'is there a residence located within a mile of the area we are planning to build the landfill?' (see DE-9IM) Geometry Constructors: Creates new geometries, usually by specifying the vertices (points or nodes) which define the shape. Observer Functions: Queries that return specific information about a feature, such as the location of the center of a circle. Some databases support only simplified or modified sets of these operations, especially in cases of NoSQL systems like MongoDB and CouchDB.

Spatial index A spatial index is used by a spatial database to optimize spatial queries, implementing spatial access methods. Database systems use indices to quickly look up values by sorting data values in a linear (e.g. alphabetical) order; however, this way of indexing data is not optimal for spatial queries in two- or three-dimensional space. Instead, spatial databases use a spatial index designed specifically for multi-dimensional ordering. Common spatial index methods include:

Binary space partitioning (BSP-Tree): Subdividing space by hyperplanes. Bounding volume hierarchy (BVH) Geohash Grid (spatial index) HHCode Hilbert R-tree k-d tree m-tree – an m-tree index can be used for the efficient resolution of similarity queries on complex objects as compared using an arbitrary metric. Octree PH-tree Quadtree R-tree: Typically the preferred method for indexing spatial data. Objects (shapes, lines and points) are grouped using the minimum bounding rectangle (MBR). Objects are added to an MBR within the index that will lead to the smallest increase in its size. R+ tree R* tree UB-tree X-tree Z-order (curve)

Spatial query A spatial query is a special type of database query supported by spatial databases, including geodatabases. The queries differ from non-spatial SQL queries in several important ways. Two of the most important are that they allow for the use of geometry data types such as points, lines and polygons and that these queries consider the spatial relationship between these geometries. The function names for queries differ across geodatabases. The following are a few of the functions built into PostGIS, a free geodatabase which is a PostgreSQL extension (the term 'geometry' refers to a point, line, box or other two or three dimensional shape): Function prototype: functionName (parameter(s)) : return type

ST_Distance(geometry, geometry) : number ST_Equals(geometry, geometry) : boolean ST_Disjoint(geometry, geometry) : boolean ST_Intersects(geometry, geometry) : boolean ST_Touches(geometry, geometry) : boolean ST_Crosses(geometry, geometry) : boolean ST_Overlaps(geometry, geometry) : boolean ST_Contains(geometry, geometry) : boolean ST_Length(geometry) : number ST_Area(geometry) : number ST_Centroid(geometry) : geometry ST_Intersection(geometry, geometry) : geometry Thus, a spatial join between a points layer of cities and a polygon layer of countries could be performed in a spatially-extended SQL statement as:

The Intersect vector overlay operation (a core element of GIS software) could be replicated as:

Spatial database management systems

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Spatial database

Start with the simplest possible case. Write down what Spatial database claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Spatial database before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Spatial database ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Spatial database

In research: Spatial database appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Spatial database in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Spatial database is common in secondary-school and first-year university syllabi. It links to neighbouring topics Geometric algorithms, Spatial databases, so understanding it makes those chapters shorter.
In everyday life: Look for Spatial database outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Spatial database in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Spatial database means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Spatial database out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Spatial database in simple terms?

Why does Spatial database matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Spatial database?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Spatial database.