A geographic information system (GIS) is a system designed to capture,
store, manipulate, analyze, manage, and present spatial or geographic
data. The acronym GIS is sometimes used for geographic information
science (GIScience) to refer to the academic discipline that studies
geographic information systems and is a large domain within the
broader academic discipline of geoinformatics. What goes beyond a
GIS is a spatial data infrastructure, a concept that has no such
In general, the term describes any information system that integrates,
stores, edits, analyzes, shares, and displays geographic information.
GIS applications are tools that allow users to create interactive
queries (user-created searches), analyze spatial information, edit
data in maps, and present the results of all these operations.
Geographic information science is the science underlying geographic
concepts, applications, and systems.
GIS can refer to a number of different technologies, processes, and
methods. It is attached to many operations and has many applications
related to engineering, planning, management, transport/logistics,
insurance, telecommunications, and business. For that reason, GIS
and location intelligence applications can be the foundation for many
location-enabled services that rely on analysis and visualization.
GIS can relate unrelated information by using location as the key
index variable. Locations or extents in the Earth space–time may be
recorded as dates/times of occurrence, and x, y, and z coordinates
representing, longitude, latitude, and elevation, respectively. All
Earth-based spatial–temporal location and extent references should
be relatable to one another and ultimately to a "real" physical
location or extent. This key characteristic of GIS has begun to open
new avenues of scientific inquiry.
1 History of development
2 GIS techniques and technology
2.1 Relating information from different sources
2.2 GIS uncertainties
2.3 Data representation
2.4 Data capture
2.5 Raster-to-vector translation
2.6 Projections, coordinate systems, and registration
Spatial analysis with geographical information system (GIS)
3.1 Slope and aspect
3.2 Data analysis
3.4 Geometric networks
3.5 Hydrological modeling
3.6 Cartographic modeling
3.7 Map overlay
3.9 Address geocoding
3.10 Reverse geocoding
3.11 Multi-criteria decision analysis
3.12 Data output and cartography
3.13 Graphic display techniques
3.14 Spatial ETL
3.15 GIS data mining
Open Geospatial Consortium
Open Geospatial Consortium standards
4.2 Web mapping
4.3 Adding the dimension of time
6 Implications of GIS in society
6.1 GIS in education
6.2 GIS in local government
7 See also
9 Further reading
10 External links
History of development
The first known use of the term "geographic information system" was by
Roger Tomlinson in the year 1968 in his paper "A Geographic
Information System for Regional Planning". Tomlinson is also
acknowledged as the "father of GIS".
E. W. Gilbert's version (1958) of John Snow's 1855 map of the
Soho cholera outbreak showing the clusters of cholera cases in the
London epidemic of 1854
Previously, one of the first applications of spatial analysis in
epidemiology is the 1832 "Rapport sur la marche et les effets du
Paris et le département de la Seine". The French
geographer Charles Picquet represented the 48 districts of the
Paris by halftone color gradient according to the number of
deaths by cholera per 1,000 inhabitants. In 1854 John Snow
determined the source of a cholera outbreak in
London by marking
points on a map depicting where the cholera victims lived, and
connecting the cluster that he found with a nearby water source. This
was one of the earliest successful uses of a geographic methodology in
epidemiology. While the basic elements of topography and theme existed
previously in cartography, the John Snow map was unique, using
cartographic methods not only to depict but also to analyze clusters
of geographically dependent phenomena.
The early 20th century saw the development of
photozincography, which allowed maps to be split into layers, for
example one layer for vegetation and another for water. This was
particularly used for printing contours – drawing these was a
labour-intensive task but having them on a separate layer meant they
could be worked on without the other layers to confuse the
draughtsman. This work was originally drawn on glass plates but later
plastic film was introduced, with the advantages of being lighter,
using less storage space and being less brittle, among others. When
all the layers were finished, they were combined into one image using
a large process camera. Once color printing came in, the layers idea
was also used for creating separate printing plates for each color.
While the use of layers much later became one of the main typical
features of a contemporary GIS, the photographic process just
described is not considered to be a GIS in itself – as the maps
were just images with no database to link them to.
Computer hardware development spurred by nuclear weapon research led
to general-purpose computer "mapping" applications by the early
The year 1960 saw the development of the world's first true
operational GIS in Ottawa, Ontario, Canada, by the federal Department
Forestry and Rural Development. Developed by Dr. Roger Tomlinson,
it was called the Canada Geographic Information System (CGIS) and
was used to store, analyze, and manipulate data collected for the
Canada Land Inventory – an effort to determine the land
capability for rural Canada by mapping information about soils,
agriculture, recreation, wildlife, waterfowl, forestry and land use at
a scale of 1:50,000. A rating classification factor was also added to
CGIS was an improvement over "computer mapping" applications as it
provided capabilities for overlay, measurement, and
digitizing/scanning. It supported a national coordinate system that
spanned the continent, coded lines as arcs having a true embedded
topology and it stored the attribute and locational information in
separate files. As a result of this, Tomlinson has become known as the
"father of GIS", particularly for his use of overlays in promoting the
spatial analysis of convergent geographic data.
CGIS lasted into the 1990s and built a large digital land resource
database in Canada. It was developed as a mainframe-based system in
support of federal and provincial resource planning and management.
Its strength was continent-wide analysis of complex datasets. The CGIS
was never available commercially.
In 1964 Howard T. Fisher formed the Laboratory for Computer
Graphics and Spatial Analysis at the Harvard Graduate School of Design
(LCGSA 1965–1991), where a number of important theoretical concepts
in spatial data handling were developed, and which by the 1970s had
distributed seminal software code and systems, such as SYMAP, GRID,
and ODYSSEY – that served as sources for subsequent commercial
development—to universities, research centers and corporations
By the late 1970s two public domain GIS systems (MOSS and GRASS GIS)
were in development, and by the early 1980s, M&S Computing (later
Intergraph) along with Bentley Systems Incorporated for the
CAD platform, Environmental Systems Research Institute (ESRI),
CARIS (Computer Aided Resource Information System), MapInfo
Corporation and ERDAS (Earth Resource Data Analysis System)
emerged as commercial vendors of GIS software, successfully
incorporating many of the CGIS features, combining the first
generation approach to separation of spatial and attribute information
with a second generation approach to organizing attribute data into
In 1986, Mapping Display and Analysis System (MIDAS), the first
desktop GIS product was released for the DOS
operating system. This was renamed in 1990 to MapInfo for Windows when
it was ported to the
Microsoft Windows platform. This began the
process of moving GIS from the research department into the business
By the end of the 20th century, the rapid growth in various
systems had been consolidated and standardized on relatively few
platforms and users were beginning to explore viewing GIS data
over the Internet, requiring data format and transfer standards. More
recently, a growing number of free, open-source GIS packages run on a
range of operating systems and can be customized to perform specific
tasks. Increasingly geospatial data and mapping applications are being
made available via the
World Wide Web
World Wide Web (see List of GIS software
§ GIS as a service).
Several articles on the history of GIS have been published.
GIS techniques and technology
Modern GIS technologies use digital information, for which various
digitized data creation methods are used. The most common method of
data creation is digitization, where a hard copy map or survey plan is
transferred into a digital medium through the use of a CAD program,
and geo-referencing capabilities. With the wide availability of
ortho-rectified imagery (from satellites, aircraft, Helikites and
UAVs), heads-up digitizing is becoming the main avenue through which
geographic data is extracted. Heads-up digitizing involves the tracing
of geographic data directly on top of the aerial imagery instead of by
the traditional method of tracing the geographic form on a separate
digitizing tablet (heads-down digitizing).[clarification needed]
Relating information from different sources
GIS uses spatio-temporal (space-time) location as the key index
variable for all other information. Just as a relational database
containing text or numbers can relate many different tables using
common key index variables, GIS can relate otherwise unrelated
information by using location as the key index variable. The key is
the location and/or extent in space-time.
Any variable that can be located spatially, and increasingly also
temporally, can be referenced using a GIS. Locations or extents in
Earth space–time may be recorded as dates/times of occurrence, and
x, y, and z coordinates representing, longitude, latitude, and
elevation, respectively. These GIS coordinates may represent other
quantified systems of temporo-spatial reference (for example, film
frame number, stream gage station, highway mile-marker, surveyor
benchmark, building address, street intersection, entrance gate, water
depth sounding, POS or CAD drawing origin/units). Units applied to
recorded temporal-spatial data can vary widely (even when using
exactly the same data, see map projections), but all Earth-based
spatial–temporal location and extent references should, ideally, be
relatable to one another and ultimately to a "real" physical location
or extent in space–time.
Related by accurate spatial information, an incredible variety of
real-world and projected past or future data can be analyzed,
interpreted and represented. This key characteristic of GIS has
begun to open new avenues of scientific inquiry into behaviors and
patterns of real-world information that previously had not been
GIS accuracy depends upon source data, and how it is encoded to be
data referenced. Land surveyors have been able to provide a high level
of positional accuracy utilizing the GPS-derived positions.
High-resolution digital terrain and aerial imagery, powerful
computers and Web technology are changing the quality, utility, and
expectations of GIS to serve society on a grand scale, but
nevertheless there are other source data that affect overall GIS
accuracy like paper maps, though these may be of limited use in
achieving the desired accuracy.
In developing a digital topographic database for a GIS, topographical
maps are the main source, and aerial photography and satellite imagery
are extra sources for collecting data and identifying attributes which
can be mapped in layers over a location facsimile of scale. The scale
of a map and geographical rendering area representation
type[clarification needed] are very important aspects since the
information content depends mainly on the scale set and resulting
locatability of the map's representations. In order to digitize a map,
the map has to be checked within theoretical dimensions, then scanned
into a raster format, and resulting raster data has to be given a
theoretical dimension by a rubber sheeting/warping technology process.
A quantitative analysis of maps brings accuracy issues into focus. The
electronic and other equipment used to make measurements for GIS is
far more precise than the machines of conventional map analysis. All
geographical data are inherently inaccurate, and these inaccuracies
will propagate through GIS operations in ways that are difficult
Main article: GIS file formats
GIS data represents real objects (such as roads, land use, elevation,
trees, waterways, etc.) with digital data determining the mix. Real
objects can be divided into two abstractions: discrete objects (e.g.,
a house) and continuous fields (such as rainfall amount, or
elevations). Traditionally, there are two broad methods used to store
data in a GIS for both kinds of abstractions mapping references:
raster images and vector. Points, lines, and polygons are the stuff of
mapped location attribute references. A new hybrid method of storing
data is that of identifying point clouds, which combine
three-dimensional points with
RGB information at each point, returning
a "3D color image". GIS thematic maps then are becoming more and more
realistically visually descriptive of what they set out to show or
For a list of popular GIS file formats, such as shapefiles, see GIS
file formats § Popular GIS file formats.
Example of hardware for mapping (
GPS and laser rangefinder) and data
collection (rugged computer). The current trend for geographical
information system (GIS) is that accurate mapping and data analysis
are completed while in the field. Depicted hardware (field-map
technology) is used mainly for forest inventories, monitoring and
Data capture—entering information into the system—consumes much of
the time of GIS practitioners. There are a variety of methods
used to enter data into a GIS where it is stored in a digital
Existing data printed on paper or PET film maps can be digitized or
scanned to produce digital data. A digitizer produces vector data as
an operator traces points, lines, and polygon boundaries from a map.
Scanning a map results in raster data that could be further processed
to produce vector data.
Survey data can be directly entered into a GIS from digital data
collection systems on survey instruments using a technique called
coordinate geometry (COGO). Positions from a global navigation
satellite system (GNSS) like
Global Positioning System
Global Positioning System can also be
collected and then imported into a GIS. A current trend in data
collection gives users the ability to utilize field computers with the
ability to edit live data using wireless connections or disconnected
editing sessions. This has been enhanced by the availability of
GPS units with decimeter accuracy in real time.
This eliminates the need to post process, import, and update the data
in the office after fieldwork has been collected. This includes the
ability to incorporate positions collected using a laser rangefinder.
New technologies also allow users to create maps as well as analysis
directly in the field, making projects more efficient and mapping more
Remotely sensed data also plays an important role in data collection
and consist of sensors attached to a platform. Sensors include
cameras, digital scanners and lidar, while platforms usually consist
of aircraft and satellites. In England in the mid 1990s, hybrid
kite/balloons called helikites first pioneered the use of compact
airborne digital cameras as airborne geo-information systems. Aircraft
measurement software, accurate to 0.4 mm was used to link the
photographs and measure the ground. Helikites are inexpensive and
gather more accurate data than aircraft. Helikites can be used over
roads, railways and towns where unmanned aerial vehicles (UAVs) are
Recently aerial data collection is becoming possible with miniature
UAVs. For example, the
Aeryon Scout was used to map a
50-acre area with a ground sample distance of 1 inch
(2.54 cm) in only 12 minutes.
The majority of digital data currently comes from photo interpretation
of aerial photographs. Soft-copy workstations are used to digitize
features directly from stereo pairs of digital photographs. These
systems allow data to be captured in two and three dimensions, with
elevations measured directly from a stereo pair using principles of
photogrammetry. Analog aerial photos must be scanned before being
entered into a soft-copy system, for high-quality digital cameras this
step is skipped.
Satellite remote sensing provides another important source of spatial
data. Here satellites use different sensor packages to passively
measure the reflectance from parts of the electromagnetic spectrum or
radio waves that were sent out from an active sensor such as radar.
Remote sensing collects raster data that can be further processed
using different bands to identify objects and classes of interest,
such as land cover.
When data is captured, the user should consider if the data should be
captured with either a relative accuracy or absolute accuracy, since
this could not only influence how information will be interpreted but
also the cost of data capture.
After entering data into a GIS, the data usually requires editing, to
remove errors, or further processing. For vector data it must be made
"topologically correct" before it can be used for some advanced
analysis. For example, in a road network, lines must connect with
nodes at an intersection. Errors such as undershoots and overshoots
must also be removed. For scanned maps, blemishes on the source map
may need to be removed from the resulting raster. For example, a fleck
of dirt might connect two lines that should not be connected.
Data restructuring can be performed by a GIS to convert data into
different formats. For example, a GIS may be used to convert a
satellite image map to a vector structure by generating lines around
all cells with the same classification, while determining the cell
spatial relationships, such as adjacency or inclusion.
More advanced data processing can occur with image processing, a
technique developed in the late 1960s by
NASA and the private
sector to provide contrast enhancement, false color rendering and a
variety of other techniques including use of two dimensional Fourier
transforms. Since digital data is collected and stored in various
ways, the two data sources may not be entirely compatible. So a GIS
must be able to convert geographic data from one structure to another.
In so doing, the implicit assumptions behind different ontologies and
classifications require analysis. Object ontologies have gained
increasing prominence as a consequence of object-oriented programming
and sustained work by Barry Smith and co-workers.
Projections, coordinate systems, and registration
Main article: Map projection
The earth can be represented by various models, each of which may
provide a different set of coordinates (e.g., latitude, longitude,
elevation) for any given point on the Earth's surface. The simplest
model is to assume the earth is a perfect sphere. As more measurements
of the earth have accumulated, the models of the earth have become
more sophisticated and more accurate. In fact, there are models called
datums that apply to different areas of the earth to provide increased
NAD83 for U.S. measurements, and the World Geodetic
System for worldwide measurements.
Spatial analysis with geographical information system (GIS)
Further information: Spatial analysis
GIS spatial analysis is a rapidly changing field, and GIS packages are
increasingly including analytical tools as standard built-in
facilities, as optional toolsets, as add-ins or 'analysts'. In many
instances these are provided by the original software suppliers
(commercial vendors or collaborative non commercial development
teams), while in other cases facilities have been developed and are
provided by third parties. Furthermore, many products offer software
development kits (SDKs), programming languages and language support,
scripting facilities and/or special interfaces for developing one's
own analytical tools or variants. The website "Geospatial Analysis"
and associated book/ebook attempt to provide a reasonably
comprehensive guide to the subject. The increased availability has
created a new dimension to business intelligence termed "spatial
intelligence" which, when openly delivered via intranet, democratizes
access to geographic and social network data. Geospatial intelligence,
based on GIS spatial analysis, has also become a key element for
security. GIS as a whole can be described as conversion to a vectorial
representation or to any other digitisation process.
Slope and aspect
Slope can be defined as the steepness or gradient of a unit of
terrain, usually measured as an angle in degrees or as a percentage.
Aspect can be defined as the direction in which a unit of terrain
faces. Aspect is usually expressed in degrees from north. Slope,
aspect, and surface curvature in terrain analysis are all derived from
neighborhood operations using elevation values of a cell's adjacent
neighbours. Slope is a function of resolution, and the spatial
resolution used to calculate slope and aspect should always be
specified. Various authors have compared techniques for
calculating slope and aspect.
The following method can be used to derive slope and aspect:
The elevation at a point or unit of terrain will have perpendicular
tangents (slope) passing through the point, in an east-west and
north-south direction. These two tangents give two components,
∂z/∂x and ∂z/∂y, which then be used to determine the overall
direction of slope, and the aspect of the slope. The gradient is
defined as a vector quantity with components equal to the partial
derivatives of the surface in the x and y directions.
The calculation of the overall 3x3 grid slope S and aspect A for
methods that determine east-west and north-south component use the
following formulas respectively:
displaystyle tan S= sqrt left( frac partial z partial x
right)^ 2 +left( frac partial z partial y right)^ 2
displaystyle tan A=left( frac left( frac -partial z partial y
right) left( frac partial z partial x right) right)
Zhou and Liu describe another formula for calculating aspect, as
displaystyle A=270^ circ +arctan left( frac left( frac partial
z partial x right) left( frac partial z partial y right)
right)-90^ circ left( frac left( frac partial z partial y right)
left frac partial z partial y right right)
It is difficult to relate wetlands maps to rainfall amounts recorded
at different points such as airports, television stations, and
schools. A GIS, however, can be used to depict two- and
three-dimensional characteristics of the Earth's surface, subsurface,
and atmosphere from information points. For example, a GIS can quickly
generate a map with isopleth or contour lines that indicate differing
amounts of rainfall. Such a map can be thought of as a rainfall
contour map. Many sophisticated methods can estimate the
characteristics of surfaces from a limited number of point
measurements. A two-dimensional contour map created from the surface
modeling of rainfall point measurements may be overlaid and analyzed
with any other map in a GIS covering the same area. This GIS derived
map can then provide additional information - such as the viability of
water power potential as a renewable energy source. Similarly, GIS can
be used to compare other renewable energy resources to find the best
geographic potential for a region.
Additionally, from a series of three-dimensional points, or digital
elevation model, isopleth lines representing elevation contours can be
generated, along with slope analysis, shaded relief, and other
elevation products. Watersheds can be easily defined for any given
reach, by computing all of the areas contiguous and uphill from any
given point of interest. Similarly, an expected thalweg of where
surface water would want to travel in intermittent and permanent
streams can be computed from elevation data in the GIS.
A GIS can recognize and analyze the spatial relationships that exist
within digitally stored spatial data. These topological relationships
allow complex spatial modelling and analysis to be performed.
Topological relationships between geometric entities traditionally
include adjacency (what adjoins what), containment (what encloses
what), and proximity (how close something is to something else).
Geometric networks are linear networks of objects that can be used to
represent interconnected features, and to perform special spatial
analysis on them. A geometric network is composed of edges, which are
connected at junction points, similar to graphs in mathematics and
computer science. Just like graphs, networks can have weight and flow
assigned to its edges, which can be used to represent various
interconnected features more accurately.
Geometric networks are often
used to model road networks and public utility networks, such as
electric, gas, and water networks. Network modeling is also commonly
employed in transportation planning, hydrology modeling, and
GIS hydrological models can provide a spatial element that other
hydrological models lack, with the analysis of variables such as
slope, aspect and watershed or catchment area. Terrain analysis is
fundamental to hydrology, since water always flows down a slope.
As basic terrain analysis of a digital elevation model (DEM) involves
calculation of slope and aspect, DEMs are very useful for hydrological
analysis. Slope and aspect can then be used to determine direction of
surface runoff, and hence flow accumulation for the formation of
streams, rivers and lakes. Areas of divergent flow can also give a
clear indication of the boundaries of a catchment. Once a flow
direction and accumulation matrix has been created, queries can be
performed that show contributing or dispersal areas at a certain
point. More detail can be added to the model, such as terrain
roughness, vegetation types and soil types, which can influence
infiltration and evapotranspiration rates, and hence influencing
surface flow. One of the main uses of hydrological modeling is in
environmental contamination research. Other applications of
hydrological modeling include groundwater and surface water mapping,
as well as flood risk maps.
An example of use of layers in a GIS application. In this example, the
forest-cover layer (light green) forms the bottom layer, with the
topographic layer (contour lines) over it. Next up is a standing water
layer (pond, lake) and then a flowing water layer (stream, river),
followed by the boundary layer and finally the road layer on top. The
order is very important in order to properly display the final result.
Note that the ponds are layered under the streams, so that a stream
line can be seen overlying one of the ponds.
Dana Tomlin probably coined the term "cartographic modeling" in his
PhD dissertation (1983); he later used it in the title of his book,
Geographic Information Systems and Cartographic Modeling (1990).
Cartographic modeling refers to a process where several thematic
layers of the same area are produced, processed, and analyzed. Tomlin
used raster layers, but the overlay method (see below) can be used
more generally. Operations on map layers can be combined into
algorithms, and eventually into simulation or optimization models.
The combination of several spatial datasets (points, lines, or
polygons) creates a new output vector dataset, visually similar to
stacking several maps of the same region. These overlays are similar
Venn diagram overlays. A union overlay combines the
geographic features and attribute tables of both inputs into a single
new output. An intersect overlay defines the area where both inputs
overlap and retains a set of attribute fields for each. A symmetric
difference overlay defines an output area that includes the total area
of both inputs except for the overlapping area.
Data extraction is a GIS process similar to vector overlay, though it
can be used in either vector or raster data analysis. Rather than
combining the properties and features of both datasets, data
extraction involves using a "clip" or "mask" to extract the features
of one data set that fall within the spatial extent of another
In raster data analysis, the overlay of datasets is accomplished
through a process known as "local operation on multiple rasters" or
"map algebra", through a function that combines the values of each
raster's matrix. This function may weigh some inputs more than others
through use of an "index model" that reflects the influence of various
factors upon a geographic phenomenon.
Main article: Geostatistics
Geostatistics is a branch of statistics that deals with field data,
spatial data with a continuous index. It provides methods to model
spatial correlation, and predict values at arbitrary locations
When phenomena are measured, the observation methods dictate the
accuracy of any subsequent analysis. Due to the nature of the data
(e.g. traffic patterns in an urban environment; weather patterns over
the Pacific Ocean), a constant or dynamic degree of precision is
always lost in the measurement. This loss of precision is determined
from the scale and distribution of the data collection.
To determine the statistical relevance of the analysis, an average is
determined so that points (gradients) outside of any immediate
measurement can be included to determine their predicted behavior.
This is due to the limitations of the applied statistic and data
collection methods, and interpolation is required to predict the
behavior of particles, points, and locations that are not directly
Hillshade model derived from a
Digital Elevation Model
Digital Elevation Model of the Valestra
area in the northern Apennines (Italy)
Interpolation is the process by which a surface is created, usually a
raster dataset, through the input of data collected at a number of
sample points. There are several forms of interpolation, each which
treats the data differently, depending on the properties of the data
set. In comparing interpolation methods, the first consideration
should be whether or not the source data will change (exact or
approximate). Next is whether the method is subjective, a human
interpretation, or objective. Then there is the nature of transitions
between points: are they abrupt or gradual. Finally, there is whether
a method is global (it uses the entire data set to form the model), or
local where an algorithm is repeated for a small section of terrain.
Interpolation is a justified measurement because of a spatial
autocorrelation principle that recognizes that data collected at any
position will have a great similarity to, or influence of those
locations within its immediate vicinity.
Digital elevation models, triangulated irregular networks,
edge-finding algorithms, Thiessen polygons, Fourier analysis,
(weighted) moving averages, inverse distance weighting, kriging,
spline, and trend surface analysis are all mathematical methods to
produce interpolative data.
Main article: Geocoding
Geocoding is interpolating spatial locations (X,Y coordinates) from
street addresses or any other spatially referenced data such as
ZIP Codes, parcel lots and address locations. A reference theme
is required to geocode individual addresses, such as a road centerline
file with address ranges. The individual address locations have
historically been interpolated, or estimated, by examining address
ranges along a road segment. These are usually provided in the form of
a table or database. The software will then place a dot approximately
where that address belongs along the segment of centerline. For
example, an address point of 500 will be at the midpoint of a line
segment that starts with address 1 and ends with
Geocoding can also be applied against actual
parcel data, typically from municipal tax maps. In this case, the
result of the geocoding will be an actually positioned space as
opposed to an interpolated point. This approach is being increasingly
used to provide more precise location information.
Reverse geocoding is the process of returning an estimated street
address number as it relates to a given coordinate. For example, a
user can click on a road centerline theme (thus providing a
coordinate) and have information returned that reflects the estimated
house number. This house number is interpolated from a range assigned
to that road segment. If the user clicks at the midpoint of a segment
that starts with address 1 and ends with 100, the returned
value will be somewhere near 50. Note that reverse geocoding does not
return actual addresses, only estimates of what should be there based
on the predetermined range.
Multi-criteria decision analysis
Coupled with GIS, multi-criteria decision analysis methods support
decision-makers in analysing a set of alternative spatial solutions,
such as the most likely ecological habitat for restoration, against
multiple criteria, such as vegetation cover or roads. MCDA uses
decision rules to aggregate the criteria, which allows the alternative
solutions to be ranked or prioritised. GIS MCDA may reduce costs
and time involved in identifying potential restoration sites.
Data output and cartography
Cartography is the design and production of maps, or visual
representations of spatial data. The vast majority of modern
cartography is done with the help of computers, usually using GIS but
production of quality cartography is also achieved by importing layers
into a design program to refine it. Most GIS software gives the
user substantial control over the appearance of the data.
Cartographic work serves two major functions:
First, it produces graphics on the screen or on paper that convey the
results of analysis to the people who make decisions about resources.
Wall maps and other graphics can be generated, allowing the viewer to
visualize and thereby understand the results of analyses or
simulations of potential events. Web Map Servers facilitate
distribution of generated maps through web browsers using various
implementations of web-based application programming interfaces (AJAX,
Java, Flash, etc.).
Second, other database information can be generated for further
analysis or use. An example would be a list of all addresses within
one mile (1.6 km) of a toxic spill.
Graphic display techniques
Traditional maps are abstractions of the real world, a sampling of
important elements portrayed on a sheet of paper with symbols to
represent physical objects. People who use maps must interpret these
symbols. Topographic maps show the shape of land surface with contour
lines or with shaded relief.
Today, graphic display techniques such as shading based on altitude in
a GIS can make relationships among map elements visible, heightening
one's ability to extract and analyze information. For example, two
types of data were combined in a GIS to produce a perspective view of
a portion of San Mateo County, California.
The digital elevation model, consisting of surface elevations recorded
on a 30-meter horizontal grid, shows high elevations as white and low
elevation as black.
Landsat Thematic Mapper image shows a false-color
infrared image looking down at the same area in 30-meter pixels,
or picture elements, for the same coordinate points,
pixel by pixel, as the elevation information.
A GIS was used to register and combine the two images to render the
three-dimensional perspective view looking down the San Andreas Fault,
using the Thematic Mapper image pixels, but shaded using the elevation
of the landforms. The GIS display depends on the viewing point of
the observer and time of day of the display, to properly render the
shadows created by the sun's rays at that latitude, longitude, and
time of day.
An archeochrome is a new way of displaying spatial data. It is a
thematic on a 3D map that is applied to a specific building or a
part of a building. It is suited to the visual display of heat-loss
Spatial ETL tools provide the data processing functionality of
traditional extract, transform, load (ETL) software, but with a
primary focus on the ability to manage spatial data. They provide
GIS users with the ability to translate data between different
standards and proprietary formats, whilst geometrically transforming
the data en route. These tools can come in the form of add-ins to
existing wider-purpose software such as spreadsheets.
GIS data mining
GIS or spatial data mining is the application of data mining methods
to spatial data. Data mining, which is the partially automated search
for hidden patterns in large databases, offers great potential
benefits for applied GIS-based decision making. Typical
applications include environmental monitoring. A characteristic of
such applications is that spatial correlation between data
measurements require the use of specialized algorithms for more
efficient data analysis.
The implementation of a GIS is often driven by jurisdictional (such as
a city), purpose, or application requirements. Generally, a GIS
implementation may be custom-designed for an organization. Hence, a
GIS deployment developed for an application, jurisdiction, enterprise,
or purpose may not be necessarily interoperable or compatible with a
GIS that has been developed for some other application, jurisdiction,
enterprise, or purpose.
GIS provides, for every kind of location-based organization, a
platform to update geographical data without wasting time to visit the
field and update a database manually. GIS when integrated with other
powerful enterprise solutions like SAP and the Wolfram
Language helps creating powerful decision support system at
enterprise level.[clarification needed]
GeaBios – tiny WMS/WFS client (Flash/DHTML)
Many disciplines can benefit from GIS technology. An active
GIS market has resulted in lower costs and continual improvements
in the hardware and software components of GIS, and usage in the
fields of science, government, business, and industry, with
applications including real estate, public health, crime mapping,
national defense, sustainable development, natural resources,
climatology, landscape architecture, archaeology, regional and
community planning, transportation and logistics. GIS is also
diverging into location-based services, which allows GPS-enabled
mobile devices to display their location in relation to fixed objects
(nearest restaurant, gas station, fire hydrant) or mobile objects
(friends, children, police car), or to relay their position back
to a central server for display or other processing.
Open Geospatial Consortium
Open Geospatial Consortium standards
Main article: Open Geospatial Consortium
Open Geospatial Consortium
Open Geospatial Consortium (OGC) is an international industry
consortium of 384 companies, government agencies, universities,
and individuals participating in a consensus process to develop
publicly available geoprocessing specifications. Open interfaces and
protocols defined by OpenGIS Specifications support interoperable
solutions that "geo-enable" the Web, wireless and location-based
services, and mainstream IT, and empower technology developers to
make complex spatial information and services accessible and useful
with all kinds of applications.
Open Geospatial Consortium
Open Geospatial Consortium protocols
include Web Map Service, and Web Feature Service.
GIS products are broken down by the OGC into two categories,
based on how completely and accurately the software follows the
OGC standards help GIS tools communicate.
Compliant Products are software products that comply to
OGC's OpenGIS Specifications. When a product has been tested
and certified as compliant through the OGC Testing Program, the
product is automatically registered as "compliant" on this site.
Implementing Products are software products that implement
OpenGIS Specifications but have not yet passed a compliance test.
Compliance tests are not available for all specifications. Developers
can register their products as implementing draft or approved
specifications, though OGC reserves the right to review and
verify each entry.
Main article: Web mapping
In recent years there has been a proliferation of free-to-use and
easily accessible mapping software such as the proprietary web
applications Google Maps and Bing Maps, as well as the free
and open-source alternative OpenStreetMap. These services give the
public access to huge amounts of geographic data; perceived by many
users to be as trustworthy and usable as professional information.
Some of them, like
Google Maps and OpenLayers, expose an application
programming interface (API) that enable users to create custom
applications. These toolkits commonly offer street maps,
aerial/satellite imagery, geocoding, searches, and routing
Web mapping has also uncovered the potential of
crowdsourcing geodata in projects like OpenStreetMap, which is a
collaborative project to create a free editable map of the world.
These mashup projects have been proven to provide a high level of
value and benefit to end users outside that possible through
traditional geographic information.
Adding the dimension of time
Historical geographic information system and Time geography
The condition of the Earth's surface, atmosphere, and subsurface can
be examined by feeding satellite data into a GIS. GIS technology
gives researchers the ability to examine the variations in Earth
processes over days, months, and years. As an example, the changes in
vegetation vigor through a growing season can be animated to determine
when drought was most extensive in a particular region. The resulting
graphic represents a rough measure of plant health. Working with two
variables over time would then allow researchers to detect regional
differences in the lag between a decline in rainfall and its effect on
GIS technology and the availability of digital data on regional
and global scales enable such analyses. The satellite sensor output
used to generate a vegetation graphic is produced for example by the
advanced very-high-resolution radiometer (AVHRR). This sensor system
detects the amounts of energy reflected from the Earth's surface
across various bands of the spectrum for surface areas of about 1
square kilometer. The satellite sensor produces images of a particular
location on the Earth twice a day. AVHRR and more recently the
moderate-resolution imaging spectroradiometer (MODIS) are only two of
many sensor systems used for Earth surface analysis.
In addition to the integration of time in environmental studies, GIS
is also being explored for its ability to track and model the progress
of humans throughout their daily routines. A concrete example of
progress in this area is the recent release of time-specific
population data by the U.S. Census. In this data set, the
populations of cities are shown for daytime and evening hours
highlighting the pattern of concentration and dispersion generated by
North American commuting patterns. The manipulation and generation of
data required to produce this data would not have been possible
Using models to project the data held by a GIS forward in time
have enabled planners to test policy decisions using spatial decision
Tools and technologies emerging from the
World Wide Web
World Wide Web Consortium's
Semantic Web are proving useful for data integration problems in
information systems. Correspondingly, such technologies have been
proposed as a means to facilitate interoperability and data reuse
among GIS applications. and also to enable new analysis
Ontologies are a key component of this semantic approach as they allow
a formal, machine-readable specification of the concepts and
relationships in a given domain. This in turn allows a GIS to focus on
the intended meaning of data rather than its syntax or structure. For
example, reasoning that a land cover type classified as deciduous
needleleaf trees in one dataset is a specialization or subset of land
cover type forest in another more roughly classified dataset can help
a GIS automatically merge the two datasets under the more general land
cover classification. Tentative ontologies have been developed in
areas related to GIS applications, for example the hydrology
ontology developed by the
Ordnance Survey in the United Kingdom
and the SWEET ontologies developed by NASA's Jet Propulsion
Laboratory. Also, simpler ontologies and semantic metadata standards
are being proposed by the W3C Geo Incubator Group to represent
geospatial data on the web.
GeoSPARQL is a standard developed by the
Ordnance Survey, United States Geological Survey, Natural Resources
Canada, Australia's Commonwealth Scientific and Industrial Research
Organisation and others to support ontology creation and reasoning
using well-understood OGC literals (GML, WKT), topological
relationships (Simple Features, RCC8, DE-9IM), RDF and the SPARQL
database query protocols.
Recent research results in this area can be seen in the International
Conference on Geospatial Semantics and the Terra Cognita –
Directions to the Geospatial Semantic Web workshop at the
Semantic Web Conference.
Implications of GIS in society
Neogeography and Public participation GIS
With the popularization of GIS in decision making, scholars have begun
to scrutinize the social and political implications of
GIS. GIS can also be misused to distort reality for
individual and political gain. It has been argued that the
production, distribution, utilization, and representation of
geographic information are largely related with the social context and
has the potential to increase citizen trust in government. Other
related topics include discussion on copyright, privacy, and
censorship. A more optimistic social approach to GIS adoption is
to use it as a tool for public participation.
GIS in education
See also: Esri Education User Conference
At the end of the 20th century, GIS began to be recognized as tools
that could be used in the classroom. The benefits of GIS in
education seem focused on developing spatial thinking, but there is
not enough bibliography or statistical data to show the concrete scope
of the use of GIS in education around the world, although the
expansion has been faster in those countries where the curriculum
GIS seem to provide many advantages in teaching geography because they
allow for analyses based on real geographic data and also help raise
many research questions from teachers and students in classrooms, as
well as they contribute to improvement in learning by developing
spatial and geographical thinking and, in many cases, student
GIS in local government
GIS is proven as an organization-wide, enterprise and enduring
technology that continues to change how local government operates.
Government agencies have adopted GIS technology as a method to better
manage the following areas of government organization:
Economic Development departments use interactive GIS mapping tools,
aggregated with other data (demographics, labor force, business,
industry, talent) along with a database of available commercial sites
and buildings in order to attract investment and support existing
business. Businesses making location decisions can use the tools to
choose communities and sites that best match their criteria for
success. GIS Planning's ZoomProspector Enterprise an Intelligence
Components software is the industry leader, servicing more than 60% of
the US population, more than 30% of Canadians, and locations in the UK
and Switzerland. You can see an example of these tools here on the
state of Pennsylvania's Department of Community and Economic
Development website, PASiteSearch.com.
Public Safety operations such as Emergency Operations Centers,
Fire Prevention, Police and Sheriff mobile technology and dispatch,
and mapping weather risks.
Parks and Recreation departments and their functions in asset
inventory, land conservation, land management, and cemetery
Public Works and Utilities, tracking water and stormwater drainage,
electrical assets, engineering projects, and public transportation
assets and trends.
Fiber Network Management for interdepartmental network assets
School analytical and demographic data, asset management, and
Public Administration for election data, property records, and
The Open Data initiative is pushing local government to take advantage
of technology such as GIS technology, as it encompasses the
requirements to fit the Open Data/Open Government model of
transparency. With Open Data, local government organizations can
implement Citizen Engagement applications and online portals, allowing
citizens to see land information, report potholes and signage issues,
view and sort parks by assets, view real-time crime rates and utility
repairs, and much more. The push for open data within
government organizations is driving the growth in local government GIS
technology spending, and database management.
Automotive navigation system
Comparison of GIS software
Digital geologic mapping
Geographic information systems in China
Geographic information systems in geospatial intelligence
GIS and aquatic science
GIS and public health
GIS in archaeology
Integrated Geo Systems
List of GIS data sources
List of GIS software
Map database management
Traditional knowledge GIS
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Media related to Geographic information systems at Wikimedia Commons
Coastal / Oceanography
Atmospheric science / Meteorology
Paleoclimatology / Palaeogeography
Geophysics / Geodesy
Earth system science
Geomorphology / Geology
Hydrology / Limnology
Integrated / Environmental
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