Copyright (c) 2006-2012 Home page: www.spatialanalysisonline.com.
GIS, like all
disciplines, utilizes a wide range of terms and abbreviations, many of which
have well-understood and recognized meanings. For a large number of commonly
used terms online dictionaries have been developed, for example: those created
by the Association for Geographic Information (AGI); the Open Geospatial Consortium (OGC); and by various software
suppliers. The latter includes many terms and definitions that are particular
to specific products, but remain a valuable resource. The
Geospatial analysis
utilizes many of these terms, but many others are drawn from disciplines such
as mathematics and statistics. The result that the same terms may mean entirely
different things depending on their context and in many cases, on the software
provider utilizing them. In most instances terms used in this Guide are defined
on the first occasion they are used, but a number warrant defining at this
stage. Table
1‑1 provides a selection of such terms, utilizing
definitions from widely recognized sources where available and appropriate.
Table 1‑1 Selected terminology
|
Definition |
|
|
Adjacency |
The sharing of a common side or boundary by
two or more polygons (AGI). Note that adjacency may also apply to
features that lie either side of a common boundary where these features are
not necessarily polygons |
|
Arc |
Commonly used to
refer to a straight line segment connecting two nodes or vertices of a
polyline or polygon. Arcs may
include segments or circles, spline functions or other forms of smooth curve.
In connection with graphs and networks, arcs may be directed or undirected,
and may have other attributes (e.g. cost, capacity etc.) |
|
Artifact |
A result
(observation or set of observations) that appears to show something unusual
(e.g. a spike in the surface of a 3D plot) but which is of no significance.
Artifacts may be generated by the way in which data have been collected,
defined or re-computed (e.g. resolution changing), or as a result of a
computational operation (e.g. rounding error or substantive software error).
Linear artifacts are sometimes referred to as “ghost lines” |
|
Aspect |
The direction in
which slope is maximized for a selected point on a surface (see also,
Gradient and Slope) |
|
Attribute |
A data item
associated with an individual object (record) in a spatial database.
Attributes may be explicit, in which case they are typically stored as one or
more fields in tables linked to a set of objects, or they may be implicit
(sometimes referred to as intrinsic), being either
stored but hidden or computed as and when required (e.g. polyline length, polygon centroid). Raster/grid datasets typically
have a single explicit attribute (a value) associated with each cell, rather
than an attribute table containing as many records as there are cells in the
grid |
|
Azimuth |
The horizontal direction of a vector, measured
clockwise in degrees of rotation from the positive Y-axis, for example,
degrees on a compass (AGI) |
|
Azimuthal
Projection |
A type of map
projection constructed as if a plane were to be placed at a tangent to the
Earth's surface and the area to be mapped were projected onto the plane. All
points on this projection keep their true compass bearing (AGI) |
|
(Spatial)
Autocorrelation |
The degree of relationship that exists between two or more (spatial)
variables, such that when one changes, the other(s) also change. This change
can either be in the same direction, which is a positive autocorrelation, or
in the opposite direction, which is a negative autocorrelation (AGI). The term
autocorrelation is usually applied to ordered datasets, such as those
relating to time series or spatial data ordered by distance band. The
existence of such a relationship suggests but does not definitely establish
causality |
|
Cartogram |
A cartogram is a form of map in
which some variable such as Population Size or Gross National Product
typically is substituted for land area. The geometry or space of the map is
distorted in order to convey the information of this alternate variable.
Cartograms use a variety of approaches to map distortion, including the use
of continuous and discrete regions. The term cartogram (or linear cartogram) is also used on occasion to refer to maps that
distort distance for particular display purposes, such as the London
Underground map |
|
Choropleth |
A thematic map [i.e. a
map showing a theme, such as soil types or rainfall levels] portraying
properties of a surface using area symbols such as shading [or color]. Area
symbols on a choropleth map usually represent categorized classes of the
mapped phenomenon (AGI) |
|
Conflation |
A term used to describe the process of
combining (merging) information from two data sources into a single source,
reconciling disparities where possible (e.g. by rubber-sheeting — see below).
The term is distinct from concatenation
which refers to combinations of data sources
(e.g. by overlaying one upon another) but retaining access to their distinct
components |
|
Contiguity |
The topological identification of adjacent
polygons by recording the left and right polygons of each arc. Contiguity is
not concerned with the exact locations of polygons, only their relative
positions. Contiguity data can be stored in a table, matrix or simply as
[i.e. in] a list, that can be cross-referenced to the relevant co-ordinate
data if required (AGI). |
|
Curve |
A one-dimensional geometric object stored as a
sequence of points, with the subtype of curve specifying the form of
interpolation between points. A curve is simple if it does not pass through
the same point twice (OGC). A LineString (or polyline — see below) is a
subtype of a curve |
|
Datum |
Strictly speaking, the singular of data.
In GIS the word datum usually relates to a reference level (surface) applying
on a nationally or internationally defined basis from which elevation is to
be calculated. In the context of terrestrial geodesy datum is usually defined
by a model of the Earth or section of the Earth, such as WGS84 (see below).
The term is also used for horizontal referencing of measurements; see Iliffe and Lott
(2008) for full details |
|
DEM |
Digital elevation
model (a DEM is a particular kind of DTM, see below) |
|
DTM |
Digital terrain
model |
|
EDM |
Electronic distance
measurement |
|
EDA, ESDA |
Exploratory data
analysis/Exploratory spatial data analysis |
|
Ellipsoid/Spheroid |
An ellipse rotated
about its minor axis determines a spheroid (sphere-like object), also known
as an ellipsoid of revolution (see also, WGS84) |
|
Feature |
Frequently used
within GIS referring to point, line (including polyline and mathematical functions
defining arcs), polygon and sometimes text (annotation) objects (see
also, vector) |
|
Geoid |
An imaginary shape for the Earth
defined by mean sea level and its imagined continuation under the continents
at the same level of gravitational potential (AGI) |
|
Geodemographics |
The analysis of
people by where they live, in particular by type of neighborhood. Such
localized classifications have been shown to be powerful discriminators of
consumer behavior and related social and behavioral patterns |
|
Geospatial |
Referring to
location relative to the Earth's surface. "Geospatial" is more
precise in many GI contexts than "geographic," because geospatial
information is often used in ways that do not involve a graphic
representation, or map, of the information. OGC |
|
Geostatistics |
Statistical methods
developed for and applied to geographic data. These statistical methods are
required because geographic data do not usually conform to the requirements
of standard statistical procedures, due to spatial autocorrelation and other problems associated with spatial
data (AGI). The term is
widely used to refer to a family of tools used in connection with spatial
interpolation (prediction) of (piecewise) continuous
datasets and is widely applied in the environmental sciences. Spatial
statistics is a term more commonly applied to the analysis of discrete
objects (e.g. points, areas) and is particularly associated with the social
and health sciences |
|
Geovisualization |
A family of
techniques that provide visualizations of spatial and spatio-temporal
datasets, extending from static, 2D maps and cartograms, to representations
of 3D using perspective and shading, solid terrain modeling and increasingly
extending into dynamic visualization interfaces such as linked windows,
digital globes, fly-throughs, animations, virtual reality and immersive
systems. Geovisualization is the subject of ongoing research by the
International Cartographic Association (ICA), Commission on
Geovisualization |
|
GIS-T |
GIS applied to
transportation problems |
|
GPS/ DGPS |
Global positioning
system; Differential global positioning system — DGPS provides improved
accuracy over standard GPS by the use of one or more fixed reference stations
that provide corrections to GPS data |
|
Gradient |
Used in
spatial analysis with reference to surfaces (scalar fields). Gradient is a
vector field comprised of the aspect
(direction of maximum slope) and slope
computed in this direction (magnitude of rise over run) at each point of the
surface. The magnitude of the gradient (the slope or inclination) is
sometimes itself referred to as the gradient (see also, Slope
and Aspect) |
|
Graph |
A
collection of vertices and edges (links between vertices) constitutes a
graph. The mathematical study of the properties of graphs and paths through
graphs is known as graph theory |
|
Heuristic |
A term derived from
the same Greek root as |
|
iid |
An abbreviation for
“independently and identically distributed”. Used in statistical analysis in
connection with the distribution of errors or residuals |
|
Invariance |
In the context of
GIS invariance refers to properties of features that remain unchanged under
one or more (spatial) transformations |
|
Kernel |
Literally, the core
or central part of an item. Often used in computer science to refer to the
central part of an operating system, the term kernel in geospatial analysis
refers to methods (e.g. density modeling, local grid analysis) that involve
calculations using a well-defined local neighborhood (block of cells,
radially symmetric function) |
|
Layer |
A collection of
geographic entities of the same type (e.g. points, lines or polygons).
Grouped layers may combine layers of different geometric types |
|
Map algebra |
A range of actions applied to the grid cells of one or more maps (or
images) often involving filtering and/or algebraic operations.
These techniques involve processing one or more raster layers according to
simple rules resulting in a new map layer, for example replacing each cell
value with some combination of its neighbors’ values, or computing the sum or
difference of specific attribute values for each grid cell in two matching
raster datasets |
|
Mashup |
A recently coined
term used to describe websites whose content is composed from multiple (often
distinct) data sources, such as a mapping service and property price
information, constructed using programmable interfaces to these sources (as
opposed to simple compositing or embedding) |
|
MBR/ MER |
Minimum bounding
rectangle/Minimum enclosing (or envelope) rectangle (of a feature set) |
|
Planar/non-planar/planar
enforced |
Literally, lying
entirely within a plane surface. A polygon set is said to be planar enforced
if every point in the set lies in exactly one polygon, or on the boundary
between two or more polygons. See also, planar graph. A graph or network with
edges crossing (e.g. bridges/underpasses) is non-planar |
|
Planar graph |
If a
graph can be drawn in the plane (embedded) in such a way as to ensure edges
only intersect at points that are vertices then the graph is described as
planar |
|
Pixel/image |
Picture element — a
single defined point of an image. Pixels have a “color” attribute whose value
will depend on the encoding method used. They are typically either binary
(0/1 values), grayscale (effectively a color mapping with values, typically
in the integer range [0,255]), or color with values from 0 upwards depending
on the number of colors supported. Image files can be regarded as a
particular form of raster or grid file |
|
Polygon |
A closed figure in
the plane, typically comprised of an ordered set of connected vertices, v1,v2,…vn-1,vn=v1 where the connections
(edges) are provided by straight line segments. If the sequence of edges is
not self-crossing it is called a simple polygon. A point is inside a simple
polygon if traversing the boundary in a clockwise direction the point is
always on the right of the observer. If every pair of points inside a polygon
can be joined by a straight line that also lies inside the polygon then the
polygon is described as being convex (i.e. the interior is a connected point
set). The OGC definition of a
polygon is “a planar surface defined by 1 exterior boundary and 0 or more
interior boundaries. Each interior boundary defines a hole in the polygon” |
|
Polyhedral surface |
A Polyhedral
surface is a contiguous collection of polygons, which share common boundary
segments (OGC). See also,
Tesseral/Tessellation |
|
Polyline |
An ordered set of
connected vertices, v1,v2,…vn‑1,vn¹v1 where the
connections (edges) are provided by straight line segments. The vertex v1
is referred to as the start of the polyline and vn as the end of the polyline. The OGC specification uses
the term LineString which it defines as: a curve with linear interpolation
between points. Each consecutive pair of points defines a line segment |
|
Raster/grid |
A data model in
which geographic features are represented using discrete cells, generally
squares, arranged as a (contiguous) rectangular grid. A single grid is
essentially the same as a two-dimensional matrix, but is typically referenced
from the lower left corner rather than the norm for matrices, which are
referenced from the upper left. Raster files may have one or more values
(attributes or bands) associated with each cell position or pixel |
|
Resampling |
1. Procedures for
(automatically) adjusting one or more raster datasets to ensure that the grid
resolutions of all sets match when carrying out combination operations.
Resampling is often performed to match the coarsest resolution of a set of
input rasters. Increasing resolution rather than decreasing requires an
interpolation procedure such as bicubic spline. 2. The process of reducing image dataset size by
representing a group of pixels with a single pixel. Thus, pixel count is
lowered, individual pixel size is increased, and overall image geographic
extent is retained. Resampled images are “coarse” and have less information
than the images from which they are taken. Conversely, this process can also
be executed in the reverse (AGI) 3. In a statistical context the term
resampling (or re-sampling) is sometimes used to describe the process of
selecting a subset of the original data, such that the samples can reasonably
be expected to be independent |
|
Rubber sheeting |
A procedure to adjust the co-ordinates all of
the data points in a dataset to allow a more accurate match between known
locations and a few data points within the dataset. Rubber sheeting …
preserves the interconnectivity or topology, between points and objects
through stretching, shrinking or re-orienting their interconnecting lines (AGI). Rubber-sheeting techniques are widely used
in the production of Cartograms (op.
cit.) |
|
Slope |
The amount of rise of a surface (change in elevation) divided by the distance
over which this rise is computed (the run),
along a straight line transect in a specified direction. The run is usually
defined as the planar distance, in
which case the slope is the tan() function. Unless the surface is flat the
slope at a given point on a surface will (typically) have a maximum value in
a particular direction (depending on the surface and the way in which the
calculations are carried out). This direction is known as the aspect. The vector consisting of the slope and aspect is the gradient of the surface at that point (see also, Gradient
and Aspect) |
|
Spatial
econometrics |
A subset
of econometric methods that is concerned with spatial aspects present in
cross-sectional and space-time observations. These methods focus in
particular on two forms of so-called spatial effects in econometric models,
referred to as spatial dependence and spatial heterogeneity (Anselin, 1988,
2006) |
|
Spheroid |
A flattened (oblate) form of a sphere, or
ellipse of revolution. The most widely used model of the Earth is that of a
spheroid, although the detailed form is slightly different from a true
spheroid |
|
SQL/Structured Query
Language |
Within GIS software SQL extensions known as
spatial queries are frequently implemented. These support
queries that are based on spatial relationships rather than simply attribute
values |
|
Surface |
A 2D geometric object. A simple surface
consists of a single ‘patch’ that is associated with one exterior boundary
and 0 or more interior boundaries. Simple surfaces in 3D are isomorphic to
planar surfaces. Polyhedral surfaces are formed by ‘stitching’ together
simple surfaces along their boundaries (OGC). Surfaces may be regarded as scalar fields,
i.e. fields with a single value, e.g. elevation or temperature, at every
point |
|
Tesseral/Tessellation |
A gridded representation of a plane surface
into disjoint polygons. These polygons are normally either square (raster),
triangular (TIN — see below), or hexagonal. These models can be built into
hierarchical structures, and have a range of algorithms available to navigate
through them. A (regular or irregular) 2D tessellation involves the
subdivision of a 2-dimensional plane into polygonal tiles (polyhedral blocks)
that completely cover a plane (AGI). The term lattice is
sometimes used to describe the complete division of the plane into regular or
irregular disjoint polygons. More generally the subdivision of the plane may
be achieved using arcs that are not necessarily straight lines |
|
TIN |
Triangulated
irregular network. A form of the tesseral model based on
triangles. The vertices of the triangles form irregularly spaced nodes.
Unlike the grid, the TIN allows dense information in complex areas, and
sparse information in simpler or more homogeneous areas. The TIN dataset
includes topological relationships between points and their neighboring
triangles. Each sample point has an X,Y co-ordinate and a surface, or Z-Value. These points are connected by
edges to form a set of non-overlapping triangles used to represent the surface.
TINs are also called irregular triangular mesh or irregular triangular
surface model (AGI) |
|
Topology |
The relative location of geographic phenomena
independent of their exact position. In digital data, topological
relationships such as connectivity, adjacency and relative position are
usually expressed as relationships between nodes, links and polygons. For
example, the topology of a line includes its from- and to-nodes, and its left
and right polygons (AGI). In mathematics, a property is said to be topological if it survives stretching
and distorting of space |
|
Transformation 1. Map |
Map transformation: A computational process of
converting an image or map from one coordinate system to another.
Transformation … typically involves rotation and scaling of grid cells, and
thus requires resampling of values (AGI) |
|
Transformation 2. Affine |
Affine transformation: When a map is
digitized, the X and Y coordinates are initially held in
digitizer measurements. To make these X,Y
pairs useful they must be converted to a real world coordinate system. The
affine transformation is a combination of linear transformations that
converts digitizer coordinates into Cartesian coordinates. The basic property
of an affine transformation is that parallel lines remain parallel (AGI, with modifications). The principal affine
transformations are contraction, expansion, dilation, reflection, rotation, shear and translation |
|
Transformation
3. Data |
Data transformation
(see also, subsection 6.7.1.10): A mathematical procedure (usually a one-to-one
mapping or function) applied to an initial dataset to produce a result
dataset. An example might be the transformation of a set of sampled values {xi}
using the log() function, to create the set {log(xi)}.
Affine and map transformations are examples of mathematical transformations
applied to coordinate datasets. Note that operations on transformed data,
e.g. checking whether a value is within 10% of a target value, is not
equivalent to the same operation on untransformed data, even after back
transformation |
|
Transformation
4. Back |
Back
transformation: If a set of sampled values {xi} has been
transformed by a one-to-one mapping function f() into the set {f(xi)}, and f() has a one-to-one
inverse mapping function f-1(),
then the process of computing f-1{f(xi)}={xi} is
known as back transformation. Example f()=ln() and f-1=exp() |
|
Vector |
1. Within GIS the
term vector
refers to data that are comprised of lines or arcs, defined by beginning and
end points, which meet at nodes. The locations of these nodes and the
topological structure are usually stored explicitly. Features are defined by
their boundaries only and curved lines are represented as a series of
connecting arcs. Vector storage involves the storage of explicit topology,
which raises overheads, however it only stores those points which define a feature
and all space outside these features is “non-existent” (AGI) 2. In mathematics
the term refers to a directed line, i.e. a line with a defined origin,
direction and orientation. The same term is used to refer to a single column
or row of a matrix, in which case it is denoted by a bold letter, usually in
lower case |
|
Viewshed |
Regions of visibility observable from one or more
observation points. Typically a viewshed will be defined by the numerical or
color coding of a raster image, indicating whether the (target) cell can be
seen from (or probably seen from) the (source) observation points. By
definition a cell that can be viewed from a specific observation point is
inter-visible with that point (each location can see the other). Viewsheds
are usually determined for optically defined visibility within a maximum
range |
|
WGS84 |
World Geodetic System, 1984 version.
This models the Earth as a spheroid with major
axis 6378.137 kms and flattening factor of 1:298.257, i.e. roughly 0.3%
flatter at the poles than a perfect sphere. One of a number of such global
models |
Note: Where cited, references are drawn from the Association for
Geographic Information (AGI), and the Open Geospatial Consortium (OGC). Square bracketed text denotes insertion by the present authors into
these definitions. For OGC definitions see: Open Geospatial Consortium Inc (2006) in References section