1 Introduction to Geographic Information Systems

What GIS connects

A geographic information system (GIS) is a computer-based system for collecting, managing, analyzing, and displaying information linked to locations on Earth. It does more than draw maps: it connects geographic features with descriptive information and helps reveal spatial patterns and relationships. For example, combining plant observations with elevation, slope, and rainfall data can help identify other places where that plant may grow.

A GIS commonly brings together hardware and software for storing, processing, and displaying data; data describing locations and their characteristics; people and procedures for collecting, maintaining, analyzing, and communicating information; and networks and services that support sharing data and maps.

GIS is used in urban planning, public health, emergency response, transportation, environmental management, utilities, and natural-resource science. A city might map buildings, roads, fire stations, and population to assess which neighborhoods are farthest from emergency services.

Maps and spatial reference

A map represents geographic information, often on a flat surface. Latitude and longitude describe positions relative to Earth using angular coordinates. A projected coordinate system represents locations on a plane, commonly with distances in meters or feet. A datum specifies the reference used to measure and locate positions. A map projection transforms positions on the curved Earth to a flat map, and every projection introduces some distortion. The appropriate projection depends on the region and purpose of the map.

These spatial references matter when combining datasets. Two layers can appear misaligned if their coordinate systems or datums differ and the GIS does not correctly transform between them. Before measuring distances or areas, check that the layers' spatial references are appropriate for both the study area and the task.

Maps simplify reality. Their scale, level of detail, symbols, colors, and labels influence what readers can see and infer. A road represented as a line on a small-scale map may be drawn as a wider area on a detailed city map. Map design should clarify the intended information without implying more precision than the data support.

How geographic data are represented

Spatial data generally combine a feature's location with attributes: descriptive or measured values associated with it. A road's attributes, for example, might include its name, number of lanes, or speed limit. Two common ways of representing spatial data are vector and raster.

Vector features

Vector data represent discrete features with coordinates:

• Points represent locations such as wells, trees, or bus stops.

• Lines represent features such as roads, streams, or pipelines.

• Polygons represent areas such as parcels, lakes, or administrative boundaries.

Each feature can be linked to a row in an attribute table. A road-line layer might include fields for street name, surface type, and speed limit.

Raster cells

Raster data divide an area into a grid of cells. Each cell stores a value, such as elevation, temperature, or land-cover class. A raster's cell size affects its spatial resolution: smaller cells can represent finer detail, while larger cells summarize broader areas. Raster data are useful for continuous surfaces and imagery; vector data are often useful for discrete objects and boundaries.

Layers and documentation

GIS projects commonly organize information into layers that can be displayed together, such as roads, streams, land cover, and neighborhoods. Each layer should have a consistent spatial reference and documented attributes. Metadata records information such as a dataset's source, date, meaning, coordinate system, quality, and limitations. This information helps users judge whether data are suitable for a particular task.

Acquiring geographic data

Geographic data may come from field surveys, GPS receivers, existing maps and databases, administrative records, or remote sensors. Remote sensing collects information about an area from a distance, commonly using sensors on satellites or aircraft that measure reflected or emitted energy. The resulting imagery can help map land cover, monitor fires, or track changes in forests and cities over time.

An image is not automatically a finished map layer. It needs a spatial reference, and interpreting its pixels may require classification or other processing. Sensor resolution, cloud cover, collection date, and classification accuracy can affect what conclusions the imagery supports.

Geocoding converts a place description, often a street address, into geographic coordinates. A geocoder may calculate an approximate position along an address range rather than locate a specific building entrance. Results therefore vary in precision; check match status and method before relying on them for detailed analysis.

Asking geographic questions

Spatial analysis uses locations, attributes, and spatial relationships to answer geographic questions. Introductory operations include:

• Query and selection: Find features that meet conditions, such as parks larger than a chosen area.

• Buffering: Create zones within a specified distance of features, such as areas within 500 meters of a bus stop.

• Overlay: Combine layers to find where conditions coincide, such as parcels inside a flood-risk area.

• Proximity and network analysis: Measure closeness or find routes through connected roads and paths.

• Raster analysis: Combine or summarize cell values, such as identifying cells with suitable elevation and rainfall conditions.

To identify possible sites for a community garden, an analyst could select publicly owned parcels, remove areas that intersect flood zones, and compare the remaining sites with nearby residential areas. The result depends on the input data, coordinate systems, definitions, and chosen thresholds—not just the software.

A reliable GIS workflow

A basic GIS workflow connects the question to suitable data, appropriate operations, and checked results:

1. Frame a question. Define what needs to be located, compared, or measured.

2. Find and inspect data. Check sources, dates, attributes, metadata, and fitness for purpose.

3. Prepare the layers. Verify coordinate systems, correct obvious errors, and organize attributes.

4. Analyze. Choose operations that match the question and record important settings.

5. Check and communicate results. Review outputs for errors, explain uncertainty, and present findings with a clear map or table.

Reliable conclusions require suitable data, correct spatial references, and attention to data quality and uncertainty. The choices made during analysis—including definitions and thresholds—also affect the result.