Geographic Information System (GIS) is a powerful tool. Although producing visualizations in the form of maps is its most common use, this dynamic, interactive and user-friendly tool has many other capabilities that complement it. Many organizations around the world use GIS for many tasks. The essential tasks include data input/creation, data management, data analysis and, of course, visualization.
Data Input and Creation
Data is the heart of any GIS system. Whether you want to create a simple map or perform complex analyses, you need spatial data. GIS data creation and input is a process of encoding data into a computer-readable format and input into a geodatabase. Geodatabase is a relational database for storing spatial data.
Spatial data (both location-specific and attribute data) come from various sources. Methods to input data into a GIS system include:
- Manual input- A single location (office building, a landmark) can be manually input into a geodatabase using its address or coordinate. Manual input can also be used to enter an outline of a parcel using distance and direction from a given starting point.
- Digitizing- Points, lines and polygons can be input into a geodatabase by tracing them from aerial imageries or tracing georeferenced scanned paper maps.
- GPS-These devices receive information from satellites and calculate their geographical locations. Field personnel can accurately and efficiently collect and store feature locations and descriptions. They can then upload the information and store it in GIS.
- Imagery-Imagery is a common and extremely useful data type in GIS. It is able to show extensive areas in varying levels of detail, including areas that are difficult to access. Images gathered via satellite, balloons and drones can be uploaded into GIS since they are already in digital format. Old imagery can be scanned and georeferenced.
Data is an asset. Many reports, including one published by the Economist, titled “The World’s most valuable resource is no longer oil, but data” are putting emphasis on effective data management.
Data management is the practice of collecting, storing and sharing data securely and efficiently.
GIS enables storing and sharing of spatial data. From buildings’ locations, property lines, water bodies, terrains and ecosystems as point, line and polygon features, along with their tabular portions describing each feature.
Effective data management helps organizations optimize the use of their most valuable resource and make data-driven decisions.
Data Analysis and Querying
GIS can solve complex location-oriented problems and offer an understanding of data from a geographic perspective through spatial analysis. Spatial analysis is a GIS process that examines, asses, evaluates and models spatial data.
Spatial analysis can answer a wide range of questions from where is the location with the highest occurrence of certain activities (crime, certain diseases) or visits to certain types of business. This provides decision-makers, in both private and public sectors, the opportunity to expand their businesses and efficiently distribute resources.
The spatial analysis process can use as many data layers as needed to answer the underlying question. With the help of Structured Query Language (SQL), users can retrieve subsets of tabular data through definition queries. Definition querying does not produce new data nor alter existing data.
Mapping and Visualization
Traditional maps are the most common practice for visualizing spatial data. In addition to paper maps, GIS also offers spatial data visualization in web-based applications. While traditional maps remain useful, web-based visualization offers many more added advantages. It is interactive. Users can add/remove data layers, and change colour schemes and symbols. Users can also zoom in and out and pan the displays around for greater/less detail and new insight. Web-based visualization also enables viewing large amounts of data.
These are only the most essential tasks of GIS. Many organizations use this powerful tool every day to address various important issues. From finding a suitable location for a new store, revealing substantial gaps in healthcare among various groups to relationships among crops, soils and climate. These solutions save companies a lot of money and help public sectors efficiently allocate resources.