GIS Fundamentals and History — Comprehensive Notes

What is GIS?

• GIS stands for Geographic Information System and is a computer-based system that integrates geography, information (data and their meaning), and systems (a collection of elements organized for a common purpose).
• GIS is used to acquire, store, retrieve, analyze, synthesize, and display geographic and related attribute data to promote understanding and assist decision-making (Kennedy, 2013).

Key Geographic Problem Concepts

• A geographic problem has a geographic dimension (a WHERE).
• Examples include:
  • Route planning with Google Maps
  • Crime mapping
  • Determining the best location to site a new park in Lockhart
  • Why ice caps on Mt. Kilimanjaro are melting
  • Finding the best route to Austin airport
  • Identifying neighborhoods with low crime rates

Features of a Geographic Problem

• Space: Location (where) of the problem
• Scale: Extent (local vs global)
• Pattern and Relationship: Distribution and relationships to geographic entities
• Rationale/Purpose: Why the problem is where it is
• Time: Does the problem and its impact change over time?

Why Study Geographic Problems?

• A large portion of daily information has a geographic component (location-based).
• Population growth leads to more and different geographic problems in type, magnitude, and characteristics.
• Geographic problems can be complex and recurring.
• GIS can aid understanding and tackling many types of geographic problems.

Basic Terminology

• Spatial: pertaining to space; denotes an area or location.
• Geographic/Geographical: pertaining to the Earth; denotes an area or location.
• Geospatial: data directly linked to specific geographic locations.

What is GIS?

• Definition components:
  • Geography: related to the Earth (including cartography, geodesy, photogrammetry, landforms, spatial statistics).
  • Information: data and their meaning; database concepts.
  • Systems: an organized collection of hardware, software, people, and procedures.
• GIS is a computer-based system.

GIS: Different Views and Scope

• GIS spans multiple domains:
  • Geography and related fields (cartography, geodesy, photogrammetry, landforms, spatial statistics).
  • Computer Science / MIS (graphics, visualization, database, system administration, security).
  • Application Areas (public administration, planning, geology, forestry, site selection, marketing, civil engineering, criminal justice, surveying, etc.).
• Classic definition emphasizes an organized collection of computer hardware/software, people, money, and infrastructure that enables acquisition, storage, retrieval, analysis, and display of geographic data to aid understanding and decision-making.

Synonyms and Nomenclature

• GIS synonyms by region:
  • Geographic Information System (US)
  • Geographical Information System (EU/UK)
  • Geomatique/Geomatics (Canada, EU)
  • Georelational Information System
• Technology-based, discipline-based, and other variants exist.

Defining GIS: Different Views

• Toolbox view (Slocum et al., 2005): automated system for capture, storage, retrieval, analysis, and display of spatial data.
• Methodology view (Walford, 1999): a methodology for asking questions about geographical data and visualizing answers.

Misconceptions about GIS

• GIS is not merely:
  • A modified CAD program
  • A simple mapping program
  • A computer package without theoretical foundation
  • A digital version of paper maps
  • Exactly the same as other information systems

Geographic Information Science (GIScience)

• GIScience is the theory and knowledge of GIS, including:
  • Data collection methods
  • Data management, storage, and entry
  • Analytical techniques
  • Visualization
  • GIS and society
  • Technological development of GIS

The Components of GIS

• Software
• People
• Hardware
• Data
• Approaches
• The system (GIS) integrates these components to enable geographic processing.

What Can a GIS Do?

• Effective data management
• Data visualization and analysis
• It helps answer questions such as:
  • Where is …?
  • What spatial patterns exist …?
  • What has changed since …?
  • What if …? (scenario analysis)

Where Do Insomniacs Live? (Illustrative Visualization)

• Visualization showing % of people reporting frequent poor sleep across locales (example map). Source links provided in the slides.

How Do You Win an Election? (Illustrative Visualization)

• Topic map showing how various issues compete for voter attention (Education, Taxes, Health Care, Jobs, Immigration, Public Safety, etc.).
• The visualization demonstrates how multiple issues compete in political landscapes and how GIS can portray spatial patterns in issue salience.

Modeling Urban Growth (Charleston, SC)

• Shows urban vs non-urban areas and water bodies over time (1973, 1990, 2000, 2010, 2020, 2030, 868 square miles etc.).
• Indicates growth in urban extent and changes in land use; axes show distance in miles with urban growth moving outward.
• Notation:
  • Urban, Non-urban, Water, Freeway, Highway layers (visual legend in the figure).

Modeling Suitability (Austin-San Antonio Corridor)

• Example: An MCES (Multi-Criteria Evaluation) suitability model for a new Toys Store.
• Data layers used include:
  • Existing Toys Outlets (Walmart, Toys R Us, Target)
  • Major roads, Interstate, US Highway, State Highway
  • County boundaries
• Suitability scale: 10 (Most Suitable) to 1 (Least Suitable).
• Variables by order of preference:
  1. Population Density
  2. Distance to Interstates
  3. Median Family Income
  4. Percent Children
  5. Distance to Competitors
  6. Owners-Tenure
• Example county identifiers and geographic context (counties like Bexar, Travis, Hays, etc.)
• Coordinate system: State Plane Texas Central; Projection: Lambert Conformal Conic; Map units: feet.

Who Uses GIS?

• Banking, Insurance, Logistics, Media, Marketing, Real Estate, Retail, Politics, Government, Homeland Security, Military, Emergency Management, Law Enforcement, Health Care, Transportation, Research, Libraries, Museums, Archaeology, Economics, Education, Agriculture, Conservation, Restoration, Mining, Engineering, Energy Exploration, Electricity, Gas, Biology, Telecommunication, Water, Wastewater, Surveying, Epidemiology, and more.

The GIS Process and Compilation

• Compilation ties to the Geographic Information System workflow: from collection to analysis.
• Spatial data collection/editing and data management are central to building a GIS database.
• The GIS process includes:
  • Define protocols
  • Collect and edit spatial data
  • Analyze
  • Decide and act
  • Report results
• Data sources can be:
  • Statistical data
  • Census data
  • Maps
  • Databases
  • Remotely sensed images
  • GPS data

Data Compilation: Primary Sources

• Primary sources involve data entry and digitization:
  • Data entry (manual coordinate capture, attribute capture, digital coordinate capture, data import)
  • Editing (manual point/line/area feature editing, manual attribute editing)
  • Automated error detection and editing
• Data management tasks include copying, subsetting, merging, versioning, data registration and projection, summarization and data reduction, and documentation.

Typical GIS Hardware and Software Components

• Hardware examples:
  • 36 in. × 48 in. table digitizer (0.001 in. resolution)
  • 12 in. × 17 in. linear array digitizer (>2000 dpi)
  • Dye sublimation printer (>2000 dpi)
  • Internet server
  • 2013 Pearson Education hardware illustration (DOLL image)
  • PC hardware: >4 GHz CPU, >6 GB RAM, >1 GB graphics RAM, >1 TB mass storage, CD/DVD/Blu-ray, mouse
• Software and tools:
  • GUI-based software and compilers (e.g., C++, Visual Basic)
  • GIS software (ArcGIS, IDRISI)
  • Image processing software (ERDAS Imagine, ENVI, eCognition)
  • Maintenance agreements for hardware/software/network
• GPS receivers (two hand-held units)

Data Compilation: Secondary Sources

• Private vendors (e.g., QuickBird, ESRI)
• Government agencies (e.g., USGS, USDA, TNRIS)
• Non-profit/NGOs (e.g., DIVA-GIS, UNEP, OpenStreetMap)

Data Integration and Layers

• Link geography with tabular data and other sources (scanned documents, images, videos)
• Organize geographic entities into distinct groups (layers), such as rivers, roads, etc.

Data Capture and the GIS Process: Time Considerations

• Data capture/input and processing is often the most time-consuming aspect of the GIS process.

Spatial Analysis: Core Concept

• Spatial Analysis is the ability to evaluate a problem based on spatial and related non-spatial characteristics.
• It is a key differentiator between GIS and desktop mapping; GIS integrates analysis with display and data management.

Spatial Analysis: Example Questions

• Which states had population greater than 10 million in 2000? (Attribute query)
• Which counties share a boundary with Nottinghamshire, UK? (Query by location)

Buffer Analysis: Distances

• Euclidean distance (straight-line) from A to B: $d<em>E = \,\sqrt{(x</em>B - x<em>A)^2 + (y</em>B - y_A)^2}$
  • Example value: $d_E = 0.89 \,\text{miles}$
• Network distance (via roads/paths) from A to B: $d<em>N = \min</em>{\text{paths } p} \sum_{e \in p} w(e)$
  • Example value: shortest path distance = $d_N = 1.2 \,\text{miles}$
• Note: Network distance reflects routes along transportation networks; Euclidean distance is a straight-line measure.

Display and Visualization

• Purpose: better communication, reveal hidden relationships, help formulate research questions; cartography overlaps with analysis.
• Map design questions include general readability, ethical considerations, and clarity of message.

Cartography and Design Rules

• When creating a map, follow cartographic design rules and conventions:
  • Choice of map projection
  • Thematic map type
  • Data representation and classification
  • Font placement
  • Color schemes
  • Perceptual considerations and the science of vision
• Cartography is essential for communicating geographic information.

A Brief History of GIS (Selected Milestones)

• Early spatial analysis: Charles Picquet’s cholera map (1832)
• John Snow’s cholera map of London (1854) – classic epidemiological GIS example
• North American development: early data sets like World Data Bank and GBF/DIME (US Census, 1967)
• General trend: GIS origins in thematic cartography and map overlay techniques; design with nature influence by Ian McHarg.

Milestones in GIS (Early Systems and Key Figures)

• CGIS (Canada Geographic Information System), 1964, Roger Tomlinson – founder called the “father of GIS.”
• MLMIS (Minnesota Land Management Information System), 1969
• LUNR (New York Land Use and Natural Resources Inventory), 1967
• Harvard University’s Laboratory for Computer Graphics and Spatial Analysis, 1960s–1970s (Odyssey project)

The Harvard Laboratory and Key Figures

• Howard Fisher: founder, developed SYMAP; background in architecture; director for initial years; contributed to thematic cartography.
• William Warntz: director who shifted focus to spatial analysis.
• Lab expansion and eventual dissolution (growth to ~40 staff by 1970; dissolved in 1991).
• The Lab’s influence on early computer mapping software and spatial analysis for environmental planning.

DIME, GBF, and TIGER: Evolution of GIS Data Formats

• Dual Independent Map Encoding (DIME): encoding scheme developed for efficient geographic data storage (US Census, 1965–1967). GBF (Geographic Base File) was the storage format.
• TIGER (Topologically Integrated Geographic Encoding and Referencing): successor to GBF, developed to support the Decennial Census; TIGER provides geospatial/map features (roads, city limits, rivers, tracts) but not census demographics; can be merged with demographics and other data sources; public domain data.
• TIGER/Line: Census Bureau format used to describe roads, highways, city limits, rivers, lakes, and census tracts.

National Center for Geographic Information and Analysis (NCGIA)

• Founded in 1988; hosted at UCSB, SUNY Buffalo, and University of Maine; funded by a $5 million NSF grant.
• Notable faculty: Michael Goodchild, Michael Batty, David Mark, A. Stewart Fotheringham, Andrew Frank, Helen Couclelis, Keith Clarke, Luc Anselin, Waldo Tobler, among others.
• Research initiatives typically started and ended with specialist meetings; publications often followed (e.g., Initiative 1: Accuracy of spatial databases; Initiative 2: Languages of Spatial Relations).

University Consortium for Geographic Information Science (UCGIS)

• An academic non-profit organization (founded 1995) promoting multidisciplinary collaboration across cartography, cognitive science, computer science, engineering, environmental sciences, geodetic science, geography, landscape architecture, law and public policy, remote sensing, statistics, and more.

Google Earth and Modern GIS Tools

• Google Earth renders a 3D representation of Earth using satellite imagery, aerial photography, and GIS data on a 3D globe.
• Features include:
  • Address/coordinate search, navigation via keyboard/mouse or touch devices
  • Ability to add data using Keyhole Markup Language (KML)
  • Web Map Service (WMS) client capabilities
  • Releases covering >97% of the Earth's surface (as of 2019)

How to Learn More

• Suggested resources for history of GIS and related topics:
  • The Remarkable History of GIS
  • The Beginnings of GIS
  • ESRI’s History of GIS
  • NCGIA – National Center for Geographic Information and Analysis
  • UCGIS – University Consortium for Geographic Information Science
  • UCGIS Body of Knowledge

Readings

• Bolstad (2022), Chapter 1

Key Equations and Concepts to Remember

• Euclidean distance between points A and B: $d<em>E = \sqrt{(x</em>B - x<em>A)^2 + (y</em>B - y_A)^2}$
• Network distance (shortest path on a network): $d<em>N = \min</em>{p \in \mathcal{P}} \sum_{e \in p} w(e)$ where p is a path and w(e) is the weight (e.g., travel distance or time) of edge e.
• Map scale, projection choices, and their influence on distance, direction, and area accuracy (cartographic implications).
• The distinction between data types: spatial (geographic features) vs non-spatial attributes (tabular data) that can be linked via keys.

Real-World Relevance and Implications

• GIS underpins decision-making in planning, public administration, geology, forestry, site selection, marketing, civil engineering, law enforcement, epidemiology, and many other fields.
• Ethical and practical considerations include accessibility of data (public domain TIGER data), privacy concerns in crime and health data, and the need for sound cartographic design to avoid misinterpretation.
• GIS enables scenario analysis (what-if questions) and helps visualize complex relationships that are not easy to discern from raw data alone.