Module 1: Introduction to GIS

1.1 What is GIS?

A precise definition of GIS, what problems it solves, and why location changes everything about a dataset.

Lesson 1 of 100·20 min read

Key takeaways

A Geographic Information System (GIS) is a framework for capturing, storing, analysing, and communicating data tied to location.

GIS is not one piece of software — it's the combination of data, hardware, software, methods, and people.

Location transforms ordinary tables into spatial data, unlocking analyses that are impossible with rows and columns alone.

Introduction

Every day, humans generate tens of billions of records that reference a place — a GPS ping from a phone, a property boundary in a city registry, a satellite image of a farm, a delivery address on a package. On their own these records are just rows of data. A Geographic Information System (GIS) is the discipline — and the software stack — that turns those location-referenced records into usable knowledge.

Formally, a GIS is a system for capturing, managing, analysing, and communicating information that has a spatial component. That "spatial component" can be explicit coordinates (latitude and longitude), an address, a postal code, a county name, or a cell in a raster grid. Anything that can be placed on a map can, in principle, be stored and analysed in a GIS.

In this opening lesson we'll untangle what GIS actually is, why it matters, and how it differs from related fields like cartography, remote sensing, and data science.

A working definition

Several classic definitions shape the field. The National Center for Geographic Information and Analysis (NCGIA) defined GIS as "a computerised database management system for the capture, storage, retrieval, analysis, and display of spatial data." Paul Longley's popular textbook calls it "a tool for revealing what is otherwise invisible in geographic information." Both are right. For this course, we'll use a slightly broader, practical definition:

A GIS is an integrated set of people, data, software, and procedures used to answer questions that depend on where.

The integration matters. A SQL database can store coordinates, but it isn't a GIS until it can perform spatial operations ("which parcels are within 500 m of a river?"). A static paper map is not a GIS either — without computation, you cannot re-query or re-analyse the data it depicts. GIS sits at the intersection of computing, geography, and decision-making.

Five defining capabilities

What separates a GIS from an ordinary database? Five capabilities:

Georeferencing — every record is tied to a real-world location through a coordinate reference system (CRS). Data from different sources can be overlaid because they share a common spatial frame.
Spatial querying — you can ask where, not just what. "How many hospitals are within a 10-minute drive of each neighbourhood?" is a spatial query.
Geometric operations — unions, intersections, buffers, distances, and other geometric functions work on shapes (points, lines, polygons) rather than numbers.
Cartographic visualisation — the system can render data as maps, choosing symbols, colour ramps, projections, and layouts appropriate to the message.
Topology and relationships — a GIS understands containment, adjacency, connectivity, and overlap between features. A road is not merely a line; it connects to other roads at specific nodes.

If a tool has all five, it's a GIS. If it has only some — a Python plotting library might cover (4) but not (2) or (3) — it's a GIS component rather than a full system.

Spatial data vs tabular data

Most business data lives in tables. A row represents a customer; columns record their name, email, and signup date. A spatial dataset extends this idea by attaching a geometry to each row:

customer_id	name	signup_date	geometry
1	Alex	2024-01-12	POINT(−122.42 37.77)
2	Maya	2024-02-03	POINT(−73.99 40.74)
3	Jonas	2024-02-14	POINT(2.35 48.86)

The geometry column is the spatial key. Once present, you can answer questions the original table could not:

Which customers live within 5 km of a store?
Which city has the highest density of customers per km²?
How far does the average package travel between warehouse and customer?

A GIS is the engine that treats geometry as a first-class citizen.

What GIS is not

It's easy to conflate GIS with neighbouring disciplines. A few distinctions:

Cartography is the art and science of making maps. Cartography predates GIS by centuries and is a subset of what a GIS does.
Remote sensing is the acquisition of data about the Earth's surface from satellites, aircraft, or drones. Remote sensing produces the raster data that GIS analyses.
Surveying and geodesy establish the coordinate frameworks and precise measurements that GIS relies on but does not create.
Spatial data science uses statistical and machine-learning methods on geographic data — it sits alongside GIS, often running inside a GIS environment.
Web mapping publishes maps on the internet. Most web maps today are fed by a GIS backend, but web mapping alone is only the display layer.

Understanding these boundaries helps you pick the right tool for a problem.

Where GIS creates value

Practically every industry consumes spatial data. A short, non-exhaustive list:

Urban planning — zoning, transportation, land-use forecasting.
Environmental science — deforestation tracking, species habitat modelling, flood mapping.
Public health — disease surveillance, accessibility of services, environmental exposure.
Logistics and retail — route optimisation, service-area analysis, site selection.
Agriculture — precision farming, crop health monitoring, yield prediction.
Defence and humanitarian response — situational awareness, damage assessment, evacuation planning.
Real estate and insurance — valuation, risk modelling, claim assessment.

Module 1.4 expands on these. The point for now: when a decision depends on where, a GIS is likely involved.

A tiny first example

Here is the smallest useful spatial query in SQL (PostGIS flavour):

SQL

1-- Which fire stations are within 2 km of a given address?
2SELECT station_id, name
3FROM fire_stations
4WHERE ST_DWithin(
5  geom,
6  ST_SetSRID(ST_MakePoint(-122.4194, 37.7749), 4326)::geography,
7  2000  -- metres
8)
9ORDER BY ST_Distance(
10  geom,
11  ST_SetSRID(ST_MakePoint(-122.4194, 37.7749), 4326)::geography
12);

Five lines of SQL, but every bit of it is GIS: a coordinate reference system (SRID 4326), geodesic distance (::geography), a spatial predicate (ST_DWithin), and a spatial ordering. Later modules unpack each concept.

Self-check exercises

1. Define GIS in one sentence, in your own words.

Any answer that captures these elements is good: a system (people + software + data + methods) for capturing, managing, analysing, and visualising information that has a location component.

2. What's the difference between a GIS and a regular database with a latitude column?

A regular database can store coordinates but cannot natively perform geometric operations (distances, overlays, containment) or render cartographic maps. A GIS understands geometry as a type, supports spatial indexes, and provides operations that treat location as a first-class property rather than two numeric columns.

3. Name three industries where GIS is essential, and one question a GIS might answer in each.

Examples: urban planning ("how much of the city is within a 10-minute walk of a park?"), agriculture ("which fields show declining crop health this season?"), public health ("which neighbourhoods have the lowest access to primary care?"). Any three reasonable pairings are fine.

Summary

GIS = people + data + software + procedures, integrated around location.
Five defining capabilities: georeferencing, spatial querying, geometric operations, visualisation, topology.
GIS overlaps with but is distinct from cartography, remote sensing, surveying, and spatial data science.
Value is created whenever a decision depends on "where."
The next lessons build the history, components, and applications to complete the mental model.