Transport Data Analysis Using GIS Training Course

Participants can align transport datasets accurately within an appropriate coordinate reference system.

• Geographic and projected coordinate systems selected for transport measurement tasks
• Datum transformations checked when combining GPS and base-map datasets
• Linear units, area distortion and scale effects assessed before analysis
• Geocoding accuracy evaluated against authoritative street and address reference data
• Route measures aligned using linear referencing and calibrated network geometry
• Metadata records capture coordinate systems, precision and transformation choices

Participants can specify fit-for-purpose transport data collection methods and IoT data requirements.

• Manual counts, surveys and observations designed with sampling and location protocols
• GPS probes, automatic vehicle location and mobile devices compared
• IoT sensor types: loops, cameras, Bluetooth, RFID and environmental monitors
• Sensor placement planned around coverage, calibration, maintenance and communications
• Collection intervals matched to congestion, dwell-time and incident analysis
• Privacy risks assessed for location traces, identifiers and passenger records

Participants can assess transport data fitness, document limitations and apply responsible handling controls.

• Completeness, accuracy, timeliness, consistency and validity assessed systematically
• Missing GPS pings, duplicate records and impossible speeds flagged
• Attribute domains and business rules applied to transport asset records
• ISO 19157 data quality concepts applied to spatial datasets
• Personal data minimisation and retention rules applied to movement records
• Quality assurance logs record corrections, assumptions and unresolved issues

Participants can prepare interoperable transport datasets for reliable spatial and temporal analysis.

• Tabular trip records joined to stops, zones and road links
• Geometry repair resolves gaps, overlaps, duplicates and invalid network features
• Field calculations standardise dates, travel times, speeds and identifiers
• Spatial joins aggregate incidents, counts and demand to network segments
• ETL workflows document source files, transformations and output naming conventions
• PostGIS tables structured for repeatable transport data loading and querying

Participants can construct and validate a routable network dataset for transport modelling.

• Network topology checks connected links, dangling nodes and prohibited movements
• Impedance attributes represent distance, time, tolls, gradients and reliability
• Turn restrictions, one-way streets and access constraints encoded correctly
• Road hierarchy and functional class support realistic routing behaviour
• Transit stops and transfer links integrated with pedestrian network connections
• Validation routes compare model outputs with observed journey conditions

Participants can clean GPS traces and derive vehicle movement measures from matched trajectories.

• Raw GPS records filtered for timestamp errors and coordinate outliers
• Map matching assigns trajectory points to probable road network links
• Trip segmentation identifies departures, arrivals, stops and dwell periods
• Speed profiles calculated by link, direction, time period and vehicle
• Trajectory aggregation reveals recurring delay locations and route deviations
• Confidence scores communicate uncertainty in matched vehicle movements

Participants can analyse traffic and fleet performance using spatially referenced operational measures.

• Travel-time reliability measured using percentile travel times and buffer index
• Link speeds compared across peak periods, weekdays and weather conditions
• Fleet utilisation mapped from vehicle availability, trips and idle time
• Dwell-time patterns analysed at stops, depots and loading locations
• Bottleneck segments ranked using delay, volume and recurrence measures
• Before-and-after comparisons control for time periods and route changes

Participants can analyse scheduled public transport service coverage, connectivity and passenger access.

• GTFS tables interpreted for routes, trips, stops, calendars and shapes
• Schedule data validated for duplicate stops, missing times and invalid coordinates
• Headways calculated by route, stop, direction and time band
• Transfer opportunities assessed using walking links and timetable windows
• Service frequency maps identify uneven provision across neighbourhoods
• Scheduled and observed running times compared using AVL records

Participants can measure access to transport services and essential destinations using network-based methods.

• Service areas generated from walking, cycling and driving travel-time thresholds
• Isochrones compare access under peak, off-peak and disruption conditions
• Population and employment data intersected with transport catchments
• Two-step floating catchment area method measures service accessibility
• Barriers such as motorways, crossings and gradients included in access models
• Equity indicators compare accessibility outcomes between demographic groups

Participants can create and interpret origin-destination patterns for transport planning and operations.

• Origin-destination matrices constructed from surveys, smartcards and GPS traces
• Desire lines mapped with aggregation rules that prevent visual clutter
• Trip generation and attraction rates calculated for analysis zones
• Zone systems reviewed for modifiable areal unit problem effects
• Temporal demand profiles distinguish commuter, freight and discretionary travel
• Market segmentation combines trip purpose, mode, time and location

Participants can model routes, stops and facility locations against operational transport constraints.

• Shortest path and fastest path compared using different impedance assumptions
• Vehicle routing considers capacity, time windows and depot constraints
• Location-allocation models identify candidate depot, hub and stop sites
• Multi-criteria suitability analysis ranks locations using weighted overlay
• Last-mile delivery zones defined from access restrictions and demand density
• Scenario assumptions documented for route changes and operational constraints

Participants can identify road safety patterns and prioritise locations for further investigation.

• Crash records geocoded and matched to intersections and road segments
• Kernel density estimation identifies concentrations of crashes and casualties
• Network kernel density accounts for events distributed along road links
• Empirical Bayes methods reduce random variation in crash rates
• Exposure measures incorporate traffic volume, vehicle kilometres and pedestrian activity
• Collision diagrams combine crash type, movement, severity and timing

Participants can detect congestion patterns and investigate incident-related network effects.

• Space-time cubes organise observations by location and reporting interval
• Emerging hot spot analysis detects persistent, intensifying and new congestion
• Incident locations linked to delay, diversion and recovery time measures
• Control charts distinguish routine variation from operational performance exceptions
• Corridor heat maps display speed degradation by time and direction
• Network impacts mapped using closure, diversion and affected-demand scenarios

Participants can select and interpret spatial statistical tests for transport patterns and relationships.

• Global Moran's I tests spatial autocorrelation in transport performance measures
• Local Indicators of Spatial Association identify statistically significant local clusters
• Getis-Ord Gi* distinguishes hot spots from cold spots
• Regression diagnostics test relationships between access, demand and service variables
• Spatial lag and spatial error models address dependent observations
• Statistical results interpreted with confidence intervals, assumptions and limitations

Participants can use imagery-derived information to support transport asset and corridor analysis.

• Satellite and aerial imagery selected by resolution, date and spectral requirements
• Image classification identifies roads, impervious surfaces and land-use change
• Change detection highlights construction, encroachment and corridor alterations
• LiDAR elevation data supports slope, drainage and visibility assessment
• Orthophoto interpretation verifies road geometry, facilities and roadside assets
• Ground truth records validate remotely sensed transport feature classifications

Participants can communicate transport findings through clear maps, indicators and decision-focused reports.

• Cartographic hierarchy directs attention to transport decisions and performance patterns
• Classification methods selected for rates, counts, indices and change measures
• Time-enabled maps communicate trends without obscuring comparison periods
• Dashboard indicators link operational targets to mapped network conditions
• Uncertainty displayed through confidence classes, notes and data-quality statements
• Technical reports distinguish findings, interpretation, recommendations and limitations

Participants can plan a sustainable transport GIS workflow with governance, automation and maintenance controls.

• Data architecture defines authoritative sources, update cycles and ownership roles
• Standard operating procedures specify collection, validation, publishing and archival steps
• ModelBuilder and QGIS Processing automate recurring geoprocessing sequences
• SQL queries extract repeatable network, trip and sensor performance indicators
• Version control principles support traceable scripts, models and documentation
• Implementation roadmaps sequence quick wins, dependencies, resources and governance

Participants can build, review and present a complete transport GIS analysis addressing a defined operational or planning decision.

• Decision question scoped with stakeholders, measures, geography and time period
• Source datasets assessed for quality, permissions, gaps and analytical fitness
• Network, GPS, transit or sensor data prepared using documented workflows
• Appropriate spatial methods selected, parameterised and checked against assumptions
• Maps, indicators and recommendations assembled for a decision-maker audience
• Peer review tests reproducibility, interpretation, limitations and presentation quality