Applied GIS Course

Lesson 1 • GIS Software Environments

Surveys desktop, web, and open-source GIS platforms and their interfaces. Students identify the right tool for different professional contexts.

Lesson 2 • What GIS Is and Why It Matters

Defines GIS, its core components, and its role across industries. Establishes the conceptual baseline for all subsequent technical work.

Lesson 3 • Spatial Thinking and Geographic Concepts

Introduces spatial reasoning, location, distance, and pattern recognition. Develops the mental framework needed to interpret geographic phenomena.

Lesson 1 • Vector Data Model

Covers points, lines, and polygons as representations of geographic features. Connects data model choice to analytical accuracy and storage efficiency.

Lesson 2 • Data Quality and Metadata

Addresses accuracy, completeness, consistency, and lineage of spatial data. Students evaluate dataset fitness before committing to analysis.

Lesson 3 • Organising and Managing GIS Projects

Establishes folder structures, naming conventions, and geodatabase organisation. Students maintain reproducible, shareable project environments.

Lesson 4 • Acquiring and Importing Spatial Data

Teaches methods for obtaining data from open portals, APIs, and field collection. Students can import and validate datasets in a GIS environment.

Lesson 1 • Symbolisation and Colour Theory

Teaches symbol selection, colour schemes, and classification methods for thematic maps. Students match visual variables to data types and map purpose.

Lesson 2 • Labeling and Annotation

Addresses automated labeling rules and manual annotation for clarity. Students produce maps where text enhances rather than clutters spatial content.

Lesson 3 • Exporting and Sharing Maps

Covers output formats, resolution settings, and sharing platforms. Students deliver maps in formats appropriate for print, web, and presentation.

Lesson 4 • Map Elements and Layout Design

Covers essential map elements including title, legend, scale bar, and north arrow. Students assemble complete, publication-ready map layouts.

Lesson 1 • Georeferencing Raster Data

Teaches alignment of scanned maps and imagery to a coordinate system using control points. Students produce georeferenced rasters ready for overlay and digitising.

Lesson 2 • Editing Existing Vector Features

Covers tools for modifying geometry and attributes of existing features. Students correct errors and update datasets to reflect current conditions.

Lesson 3 • Digitising from Imagery and Basemaps

Teaches on-screen digitising of points, lines, and polygons from aerial and satellite imagery. Students create new vector layers aligned to real-world features.

Lesson 1 • Spatial Joins and Table Operations

Covers spatial joins, table joins, and field calculations for enriching datasets. Students link attribute information across layers based on location.

Lesson 2 • Geoprocessing Overlay Tools

Teaches clip, intersect, union, erase, and identity operations on vector layers. Students combine datasets to reveal spatial relationships and patterns.

Lesson 3 • Dissolve, Merge, and Append Operations

Explains tools for combining and simplifying feature datasets. Students streamline datasets and prepare inputs for downstream analysis.

Lesson 4 • Proximity and Buffer Analysis

Covers buffer creation, multiple-ring buffers, and near-distance calculations. Students quantify spatial relationships based on distance thresholds.

Lesson 1 • Raster to Vector Conversion and Integration

Covers converting raster outputs to vector features and integrating both data models. Students combine raster analysis results with vector datasets for comprehensive outputs.

Lesson 2 • Terrain Analysis from Digital Elevation Models

Derives slope, aspect, hillshade, and curvature from elevation data. Students characterise terrain for environmental, engineering, and planning applications.

Lesson 3 • Raster Calculator and Map Algebra

Introduces cell-by-cell mathematical operations across raster layers. Students combine rasters to create derived datasets for multi-criteria analysis.

Lesson 4 • Reclassification and Suitability Modelling

Covers reclassifying raster values and weighting layers for suitability analysis. Students build weighted overlay models to rank locations by multiple criteria.

Lesson 1 • Data Sharing and Interoperability

Addresses data exchange formats, web services, and interoperability standards. Students publish and consume spatial data across platforms and organisations.

Lesson 2 • Geodatabase Design and Structure

Covers feature datasets, feature classes, domains, and subtypes in geodatabase design. Students create structured, rule-enforced data schemas for organisational use.

Lesson 3 • Geoprocessing Automation with ModelBuilder

Introduces ModelBuilder for creating visual geoprocessing workflows. Students automate multi-step analyses and share repeatable processes with colleagues.

Lesson 4 • Relationship Classes and Data Integrity

Teaches relationship classes that link tables and enforce referential integrity. Students model real-world associations between spatial and non-spatial data.

Lesson 1 • Environmental and Land Use Analysis

Applies GIS to analyse land cover change, habitat connectivity, and environmental impact. Students produce evidence-based assessments for planning and conservation decisions.

Lesson 2 • Site Suitability and Location Analysis

Applies overlay, raster suitability, and proximity methods to real site-selection problems. Students produce ranked location recommendations supported by spatial evidence.

Lesson 3 • Documenting and Presenting GIS Work

Teaches technical reporting, map series production, and stakeholder presentation skills. Students communicate spatial findings clearly to both technical and non-technical audiences.

Lesson 4 • Infrastructure and Network Analysis

Covers network datasets, routing, and service area analysis for infrastructure planning. Students optimise routes and assess coverage gaps in transportation or utility networks.