CONTRIBUTING DISCIPLINES
GIS is a convergence of technological fields and traditional disciplines. GIS has been called an ‘enabling technology’ because of the potential it offers for the wide variety of disciplines which must deal with spatial data. Each related field provides some of the techniques which make up GIS. Many of these related fields emphasize data collection – GIS brings them together by emphasizing integration, modelling and analysis, as the integrating field, GIS often claims to be the science of spatial information.
Geography: Geography is broadly concerned with understanding the world and man’s place in it. Geography has long tradition in spatial analysis. The discipline of geography provides techniques for conducting spatial analysis and a spatial perspective on research.
Cartography: Cartography is concerned with the display of spatial information. Currently it is the main source of input data for GIS is maps. Cartography provides long tradition in the design of maps which is an important form of output from GIS. Computer cartography (also called ‘digital cartography’, ‘automated cartography’) provides methods for digital representation and manipulation of cartographic features and methods of visualization.
Remote Sensing: This emerging technique which records images from space and the air are major source of geographical data. Remote sensing includes techniques for data acquisition and processing anywhere on the globe at low cost, consistent update potential. The main advantage of it is that interpreted data from a remote sensing system can be merged with other data layers in a GIS.
Photogrammetry: Using aerial photographs and techniques for making accurate measurements
from them, photogrammetry is the source of most data on topography (ground surface elevations) used for input to GIS.
Surveying: Surveying is concerned with the measurement of locations of objects on the Earth’s surface, particularly property boundaries. Surveying provides high quality data on positions of land boundaries, buildings, etc.
Statistics: Many models built using GIS are statistical in nature, many statistical techniques used for analysis in GIS. Statistics is important in understanding issues of error and uncertainty in GIS data.
Computer Science: Computer science is one of the main engines for GIS development. Artificial intelligence (AI) uses the computer to make choices based on available data in a way that is seen to emulate human intelligence and decision-making – computer can act as an ‘expert’ in such functions as designing maps, generalizing map features. Computeraided design (CAD) provides software, techniques for data input, display and visualization, representation, particularly in 3 dimensions. Advances in computer graphics provide hardware, software for handling and displaying graphic objects, techniques of visualization. Similarly, database management systems (DBMS) contribute methods for representing data in digital form, procedures for system design and handling large volumes of data, particularly access and update.
Mathematics: Several branches of mathematics, especially geometry and graph theory, are used in GIS system design and analysis of spatial data.
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GIS is a convergence of technological fields and traditional disciplines. GIS has been called an ‘enabling technology’ because of the potential it offers for the wide variety of disciplines which must deal with spatial data. Each related field provides some of the techniques which make up GIS. Many of these related fields emphasize data collection – GIS brings them together by emphasizing integration, modelling and analysis, as the integrating field, GIS often claims to be the science of spatial information.
Geography: Geography is broadly concerned with understanding the world and man’s place in it. Geography has long tradition in spatial analysis. The discipline of geography provides techniques for conducting spatial analysis and a spatial perspective on research.
Cartography: Cartography is concerned with the display of spatial information. Currently it is the main source of input data for GIS is maps. Cartography provides long tradition in the design of maps which is an important form of output from GIS. Computer cartography (also called ‘digital cartography’, ‘automated cartography’) provides methods for digital representation and manipulation of cartographic features and methods of visualization.
Remote Sensing: This emerging technique which records images from space and the air are major source of geographical data. Remote sensing includes techniques for data acquisition and processing anywhere on the globe at low cost, consistent update potential. The main advantage of it is that interpreted data from a remote sensing system can be merged with other data layers in a GIS.
Photogrammetry: Using aerial photographs and techniques for making accurate measurements
from them, photogrammetry is the source of most data on topography (ground surface elevations) used for input to GIS.
Surveying: Surveying is concerned with the measurement of locations of objects on the Earth’s surface, particularly property boundaries. Surveying provides high quality data on positions of land boundaries, buildings, etc.
Statistics: Many models built using GIS are statistical in nature, many statistical techniques used for analysis in GIS. Statistics is important in understanding issues of error and uncertainty in GIS data.
Computer Science: Computer science is one of the main engines for GIS development. Artificial intelligence (AI) uses the computer to make choices based on available data in a way that is seen to emulate human intelligence and decision-making – computer can act as an ‘expert’ in such functions as designing maps, generalizing map features. Computeraided design (CAD) provides software, techniques for data input, display and visualization, representation, particularly in 3 dimensions. Advances in computer graphics provide hardware, software for handling and displaying graphic objects, techniques of visualization. Similarly, database management systems (DBMS) contribute methods for representing data in digital form, procedures for system design and handling large volumes of data, particularly access and update.
Mathematics: Several branches of mathematics, especially geometry and graph theory, are used in GIS system design and analysis of spatial data.
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