What is a Geographic Information System (GIS)

By GeoLayers.co.za Editorial • 2025-10-02

Contents

1. Defining GIS?
2. GIS Components
3. A short history of GIS
4. Geospatial Data
5. Coordinate systems
6. Vector data model
7. Raster data model
8. GIS Operations
9. Web Mapping
10. Industry Use of GIS
11. GIS Software
12. What to consider when creating maps

Defining GIS

Defining GIS?

To define GIS, we must first have a look at the three words that make up GIS and describe them separately. They are; Geography, Information, and System. Geography is the study of physical features, places, and the relationships between people, their environments, and distribution of populations and resources on planet Earth. Information, here, relates to details and knowledge about a particular place and a System consists of a complex whole of interconnected parts working together as a mechanism to complete certain task. When we put these definitions together, we define a Geographic Information System (GIS) as a computer based program designed to capture, store, query, analyze and present data that is associated with location. GIS has the ability to combine spatial data (information that shows the physical location of objects) and non-spatial data (information without a location component) to create digital maps. As a geographical analysis tool, GIS has the ability to integrate spatial and non-spatial data sets within a single system and offers a constant framework for analyzing geographic data. By putting maps and other kinds of spatial data into digital format, GIS allows us to;

Manipulate and display geographic knowledge into new and innovative ways.

Makes connections between activities and geographic proximity

By looking at data geographically, one can suggest new insights and explanations which are often unrecognized without GIS, but can be vital to the understanding and managing of resources and activities.

Practical Applications of GIS

GIS is being used in a wide range of industries since it's inception in the early 60's. In natural resource management, it is used in the management of rivers, recreation resources, floodplains, wetlands, agricultural land, aquifers, forest and wildlife habitat analysis. Professionals also use GIS when conducting Environmental Impact assessments (EIA's) study's, view-shed analysis, hazardous or toxic facility siting, groundwater modelling and contamination tracking as well as wildlife migration tracking. GIS is also used in facilities management to locate underground pipe and cables, balance loads in electrical networks, plan facility maintenance and track energy use. One of the more popular applications of GIS is in the administration of land records. Here, GIS is used to review zoning and subdivision plans, handle land acquisition applications, monitor water quality management, and maintenance of land ownership. GIS is also commonly used to find locations given the street address. In property development, GIS assists professionals in site selection, site identification and analysis, and development of evacuation plans.

As we can see from the list of practical application, multiple industries are beginning to understand the important role that location based intelligence has to play in their day to day activities, whether used to obtain environmental information about a particular site or finding the optimal route for a delivery service, GIS has the capabilities to bring together multiple types of information into a single system to enable decision makers to make informed decisions. Another exciting part about GIS is its integration with the internet, GPS, wireless technology and web services. You probably use GIS technology on a daily basis without even knowing it. For example, online mapping websites allow users to find real estate listings, restaurants, and hotels, social media platforms use geotagging to get locations, navigation systems provide turn by turn guidance and optimal routes, and mobile phone users can search for location information and be able to track vehicles, friends or the elderly. As GIS gets more popular, more uses will be devised to solve real world problems.

To use GIS more effectively, we first need to have an understanding of Geospatial data. Geospatial data describes both the location and characteristics of spatial features. To describe a river for example, we refer to its location, where is it? and its characteristics, how deep is it? or what type of fish are in it and for how many kilometers does it run. GIS is distinguished from other information systems because of its ability to process and integrated Geospatial data with other types of data sets. Geospatial technology can help create large databases of geographic information and turn the information into maps and decision-making tools for problem solving. We will discuss Geospatial data in more details in the following sections.

GIS Components

A fully functioning GIS comprises of four components, apart from geospatial data;

1. Hardware includes computers, workstations, and operating systems such as windows, Linux or UNIX. Other hardware components may include, display monitors, GPS (Global Positioning System) receivers, scanners and printers as well as mobile devices for field work.
2. Software includes the source code and graphical user interface. Usually written in python or C++. Common user interfaces are menus, icons and command lines.
3. People play a critical role in GIS. GIS professionals define the purpose and objectives of GIS, they provide the reason and justification for using GIS, and determine how GIS can be utilized to achieve the desired outcomes.
4. Infrastructure is the necessary physical, organizational, administrative, and cultural environments that support GIS operations. The infrastructure also includes skills, data standards, data clearinghouses, and general organizational patterns.

A short history of GIS

Geographic Information Systems (GIS) have a rich and fascinating history that spans several decades. The origins of GIS can be traced back to the early 1960s when the first computer-based GIS was developed by Roger Tomlinson in Canada. Tomlinson's system, known as the Canada Geographic Information System (CGIS), was designed to manage and analyze data related to the country's natural resources. In the following years, GIS technology evolved rapidly, and by the 1970s, computerized GIS had become a popular tool for managing and analyzing spatial data. The development of computer hardware and software, especially the introduction of the personal computer in the 1980s, made GIS more accessible to a wider audience. This development led to the creation of new software and tools that made it easier to manipulate and analyze spatial data, and to visualize it in new and exciting ways.

During the 1990s, GIS technology was integrated with other technologies, such as remote sensing, GPS, and the internet, enabling users to access and share spatial data easily. This development made GIS more widely available and helped to expand its applications beyond traditional fields such as geography and natural resource management. Since then, GIS has become an essential tool for a wide variety of industries, including environmental management, urban planning, transportation, marketing, and many others. In recent years, GIS technology has continued to evolve and expand, driven by advances in computing power, data storage, and communication technologies. Today's GIS applications offer a wide range of capabilities, including real-time data visualization, predictive modeling, and advanced spatial analysis. GIS is an essential tool for decision-making, providing valuable insights into complex spatial relationships and patterns. Its applications continue to expand, driven by the growing need for accurate, up-to-date, and easily accessible spatial data.

Geospatial Data

As mentioned in the above sections, geospatial data is data that describes both the location and characteristics of spatial features on the surface of the Earth. This property alone distinguishes it from other types of data. To effectively use geospatial data in GIS, we must first have some kind of understanding of coordinate systems and the different spatial data models the distinguish geospatial data from other types of data. The two data models discussed here include the Vector Data Model and the Raster Data Model.

Coordinate systems

Geospatial data are geographically referenced, which means that they have a location component attached to their attributes. Every spatial feature on the Earth's surface are referenced with a geographic coordinate system in terms of latitude and longitude, which are defined by using the spherical or ellipsoidal model of the earth. However, when we plot these features on a map, they are represented in terms of a projected coordinate system which is measured in terms of x and y coordinates. The two spatial reference systems, geographic and projected, are connected by the process known as projection. A projected coordinate system uses a flat surface to represent the earth. Today, there are literally thousands of geographic and projected coordinate systems in use. Therefore, it is important to have a basic understanding of which system to use in any given scenario to ensure accuracy and consistency in your workflow or within the team.

Vector Data Model

A data model defines how Spatial features are represented. There are two types of data models used in GIS today; the Vector Data Model and the Raster data model. The vector data model uses points, lines and polygons, and their x-,y-coordinates to represent discrete features, with a clear spatial reference and a well defined boundary. Examples of vector data are point features that may represent a well, tree, or fire hydrant, line features that represent a road or river, and polygon features that may represent features such as land parcels and political boundaries. Depending on the data structure, a vector data model can be a georelational or object based data model. The georelational data model stores geometries and attributes of spatial features separately and uses the features ID's to link them. The object-based data model, which is a more recent development, stores geometries and attributes in a single system and treats spatial features as objects with associated properties and methods. Calculations such as finding the area of a park or the length of a road can be performed with much ease on vector data because a line segment or a properly defined boundary allows for precise calculations of features. It is also easy to edit and modify vector data because it is presented as points, lines and polygons, you can add, delete or modify features without affecting the rest of the data.

Raster Data Model

A raster data model uses a grid and grid cells/pixels to represent continuous features. An example where one would use a raster data model would be to show features such as temperature, elevation or precipitation. Each cell in the grid has a value that captures the magnitude of the continuous surface at the cell location. The raster data model has not changed in terms of its concept and structure since the beginning of GIS, however, methods of storing and compressing raster data types continue to evolve to this day. Raster data has the ability to represent continuous data over large areas. This is why it is the perfect data type for remote sensing and images analysis applications. Because of this ability however, it would not be the best choice to represent sharp boundaries or complex shapes. In such cases, the vector data model would be the preferred choice. There are many ways of creating a raster, let's have a look at a few examples. First is the over-head method, this is one of the more complex ways to create raster data. The values that are to be assigned to each cell in the raster are coded into a ASCII file. The ASCII file can be created by using a code editor, word processor, database or a spreadsheet program. Once coded, the file is then imported into a GIS to be processed and reformatted. This method requires professional experience and coding skills so it might not apply to a lot of users. The easiest way is to use raster that already exists. A lot of raster data already exists in digital form as images, TINs etc. Most of this data has been created using remote sensing techniques which generates images that are easier to import into a GIS.

GIS Operations

GIS operations related to the various activities that GIS professionals are engaged in on a daily basis to achieve their goals. Among these are; data input, data management, data analysis, data display, data exploration and GIS modeling.

Data input/entry involves the use of existing data or creating new data-sets. This can include digitizing paper maps, importing data from GPS receivers, or downloading data from online sources. A newly digitized map requires editing and geometric transformation. Editing removes digitizing errors from the map such as missing polygons, or topological errors, such as unclosed polygons. Geometric transformation converts the digitized map into a projected coordinated system. Once the data has been added, it usually requires a projection and re-projection to ensure the data displays in the right location

Data management or attribute data management involves entry and verification of geospatial data-sets , database management and attribute data manipulation. We use a relational data-base model to manage attribute data. A relational database is a collection of tables(relations),which can be separately prepared, maintained and edited, although these tables can be joined or related for data search or retrieval within the GIS.

Data Exploration is usually done before data analysis and involves exploring the general trends and patterns in data, taking a close look at data subsets, and finding possible relationships among data sets. On windows operating system, GIS allows for the creation and display of maps, graphs and tables in multiple but dynamically linked windows so that when a data subset is selected from the attributes table, the corresponding features in the maps or graphs are automatically highlighted. This type of interactivity increases the capacity for information processing and synthesis. Data exploration in GIS can be approached from spatial data or attribute data, or in most instances both.

Data Analysis allows users and professionals to analyze geospatial data and obtain information from it for decision making. In GIS, there are seven (7) ways in which data can be analyzed;

1. Vector data analysis is used to manipulate and analyze vector data. As mentioned, performing calculations on vector data is easy and produces more accurate results because of the structure of the data. Vector analysis includes various GIS operations such as buffering, overlay, spatial statistic, selecting, querying, distance measurements, editing and transforming data. Buffering creates buffer zones by measuring straight line distances from selected features. Overlay creates an output by combining geometries and attributes from different layers. Distance measurement calculates the distances between spatial features. Spatial statistics detects spatial dependence and patterns of concern among features and feature manipulation or data transforming tools manage and alter spatial features in a layer. These operations allow professionals to obtain information about the distribution and characteristics of spatial and geographic features such as measuring the length of a freeway or calculating the area of a sports field. Vector data analysis is done by a wide range of fields such as urban planning, natural resource management and emergency planning and response
2. Raster Data Analysis operations are commonly grouped into four categories, these include; local, neighborhood, zonal, and global operations. A local operation operates on individual cells. A new layer is created from one or more input layers by defining the value of each new pixel by the value of the same pixel on the input layer(s). In terms of the neighborhood operation, the value of a pixel on the new layer is determined by the local neighborhood of the pixel on the older layer. Filtering operates by moving a "window" across the entire raster e.g. windows are 3 x 3 cells. Operations on zones on there other hand involve identifying the zones by comparing adjacent pixels and selecting all patches or zones that have the same value. Once selected, we then give each patch or zone a unique number that will correspond to each pixel value. Next, we measure the area of each zone and assign this value to each pixel instead on the zone's number, alternatively the output may be in the form of a summary table sent to the printer or a file. Perimeter of zones measures the perimeter of each zone and assigns this value to each pixel instead of each zone. The length of the perimeter is determined by summing the number of exterior cell edges of each cell. Distance from zone boundary measures the distance from each pixel to the nearest part of its zone boundary, and assign this value to the pixel. The boundaries are defined as the pixels which are adjacent to pixels of different values. And finally, shape of zone measures the shape of the zone and assigns this value to each pixel in the zone. The most common way of measuring shape is by comparing the perimeter length of a zone to the square root of its area. By dividing this number by 3.54, we get a measure which ranges from 1 to circle (the most compact shape) to 1.13 for a square to large numbers for long, thin, wiggly zones.
3. Terrain Mapping and Analysis has for many years been the major objective for mapping and analysis for hundreds or years. Cartographers have used mapping techniques such as contouring, profiling, hill shading, and 3-D views to visualize land surface. Topographic measures such as slope analysis, aspect and surface curvature are important for studies of timber management, soil erosion, hydrological modelling, wildlife habitat suitability, and other fields. In real world examples terrain analysis can help planners to identify potential hazards such as landslides or flooding caused by heavy rainfall as well as be able to prepare evacuation or reinforcement plans.
4. Viewshed and Watershed are two important concepts in GIS, particularly in terrain analysis. A viewshed analysis determines areas of land surface that are visible from one or more observation points. A watershed analysis can derive topographical features such as flow direction, stream networks, and watershed boundaries for hydrological applications.
5. Geocoding and Dynamic Segmentation - Geocoding is the process of converting street addresses and intersections into point features were as dynamic segmentation plots linearly referenced data on a coordinate system. Both of the techniques can be used to to locate data from as source that lack x- y- coordinates and they both use linear features as reference data. Features such as streets and highways may by used in this instance.
6. Path and Network Analysis - Path analysis finds the least-cost path between cells and defines the cost for moving through each cell. Network analysis solves the shortest paths between stops on a topological network. The two analyses share the same algorithm for solving problems but differ in applications. Path analysis is raster-based and works with virtual paths, whereas network analysis is vector bases and works with existing network.

Data output/display involves the creation of maps, reports, and other visualizations that communicate the results of GIS analysis. This can include tasks such as cartography, layout design, and map production. A map usually has a number of elements: title, subtitle, body, legend, north arrow, acknowledgement, neat line, and border.

Overall, GIS operations are critical to the effective use of a geographic information systems and are essential for making informed decisions in a wide range of applications.

Web Mapping

Web mapping is the process of creating, publishing, and sharing maps and geospatial data on the internet. It allows users to interact with data and create maps using a web browser, providing a much easier way of displaying and interacting with location data, as opposed to the traditional desktop GIS. In recent years, Web mapping technology has evolved significantly, with the development of web mapping platforms such as Google Maps, OpenStreetMap, and ArcGIS Online paving the way. These platforms are providing users with a wide range of tools and functionality to carry out a variety of tasks. There are many industries that are using web based GIS systems and many more will follow suite. Some of these industries include; urban planning, transportation management, environmental monitoring, disaster response, and public health. Web mapping has become a powerful tool for visualizing and understanding complex spatial data, and is now an essential part of modern geospatial analysis.

The future of web GIS is a topic of great interest to GIS professionals and researchers alike. There are several key trends that are driving the evolution of this field and shaping its future direction. One of the most important trends is the move towards cloud-based solutions. This allows for greater scalability, flexibility, and collaboration in the use of geospatial data. Cloud-based solutions also allow for more efficient processing and analysis of large datasets, which is critical for many applications such as disaster response, urban planning, and environmental monitoring. Another important trend is the use of mobile devices for data collection and dissemination. This has the potential to revolutionize the way that geospatial data is collected and shared, particularly in remote or hard-to-reach areas. Mobile devices can be used to collect data in real-time, which can then be integrated into web GIS platforms for analysis and visualization.

The use of machine learning and artificial intelligence in web GIS is also a rapidly growing trend. These technologies can be used to automate many tasks such as classification, feature extraction, and predictive modeling, allowing GIS professionals to focus on more complex analyses and decision-making. This has the potential to greatly improve the efficiency and accuracy of geospatial analysis, as well as enable new applications such as automated land cover mapping and predictive modeling of disease outbreaks. Overall, the future of web GIS is very promising, with many exciting opportunities and challenges ahead. As the world becomes increasingly connected and data-driven, the ability to effectively collect, analyze, and communicate geospatial information will become increasingly important for businesses, governments, and individuals alike.

GIS Software

GIS software is the backbone of GIS technology. There are many different GIS software applications available, each with their own strengths and weaknesses. Some of the most popular GIS software include ArcGIS, QGIS, GRASS, MapInfo, and OpenLayers.

ArcGIS is a proprietary software developed by ESRI and is widely used in many industries. It is known for its robust functionality and user-friendly interface. ArcGIS is used for data management, mapping, analysis, and visualization. It is a comprehensive GIS software that offers a wide range of tools and features for GIS professionals.

QGIS is an open-source software that provides similar functionality to ArcGIS but is free to use. It is a powerful GIS software that offers a wide range of tools and features for data management, mapping, analysis, and visualization. QGIS is known for its flexibility and customization options, making it a popular choice among GIS professionals.

GRASS is another open-source GIS software that is more focused on scientific research and environmental modeling. It is known for its advanced analysis tools and is used mainly for scientific research and environmental modeling.

MapInfo is a desktop GIS software that is used mainly for mapping and visualization. It is known for its easy-to-use interface and is used mainly by non-GIS professionals who need to create maps and visualizations

OpenLayers is a web-based GIS software that allows users to create and share interactive maps on the web. It is known for its flexibility and customization options and is used mainly by web developers who need to create web-based maps and applications.

The choice of GIS software depends on the specific needs and requirements of the user. GIS software plays a critical role in GIS technology and is used to manage and analyze geographic information. The different types of GIS software available offer a wide range of features and capabilities, making GIS technology a versatile and powerful tool for many different industries.

What to consider when creating maps

There are many kinds of maps, each with general and possibly specific requirements. While a skilled cartographer is usually required to make maps with specific or special requirements, anyone can make good general and informative maps by considering the following simple guidelines. These guidelines can be uses as a checklist for creating or improving your maps.

1. Purpose: Determine the purpose of the map and what information needs to be conveyed. This will help in selecting the appropriate data and design for the map.
2. Audience: Consider who the map is intended for and their level of familiarity with the area being mapped. This will help in determining the level of detail and complexity of the map.
3. Scale: Choose an appropriate scale for the map based on the size of the area being mapped and the level of detail required.
4. Data: Select reliable and accurate data sources for the map. Ensure that the data is up-to-date and relevant to the purpose of the map
5. Design: Use a clear and simple design that makes the information easy to understand. Consider the use of colors, symbols, and labels to enhance the visual appeal and clarity of the map.
6. Legend: Include a legend that explains the symbols, colors, and other features used on the map. This will help the audience understand the map more easily.
7. Projection: Choose an appropriate map projection that accurately portrays the area being mapped. Different projections can distort the shapes and sizes of features on the map.