GIS for Urban Planning Training Course

Participants can select, transform and verify coordinate reference systems for urban datasets.

• Geographic and projected coordinate reference systems compared for city analysis
• EPSG codes used to document coordinate reference system choices
• Datum transformations assessed before combining survey, imagery and legacy datasets
• UTM zones and local grids selected for distance and area measurement
• Georeferencing scanned plans using ground control points and residual errors
• Positional accuracy, scale and minimum mapping unit interpreted for planning outputs

Participants can design a geospatial data model and assess candidate planning data sources.

• Feature classes, rasters, tables and relationships structured in a geodatabase
• Entity-relationship models defined for parcels, buildings, roads and service assets
• Authoritative datasets distinguished from volunteered, commercial and open geographic data
• OpenStreetMap data evaluated for completeness, currency, licensing and local verification
• Data dictionaries specify field names, domains, units and permitted values
• Metadata captured using ISO 19115 elements for source and lineage

Participants can prepare urban spatial data for analysis using repeatable quality controls.

• Tabular planning records joined using stable identifiers and relationship keys
• Geocoding address records with match scores and exception review
• Digitising parcels, building footprints and zoning boundaries from reference imagery
• Topology rules detect gaps, overlaps, slivers and invalid boundary relationships
• Attribute domains and validation rules prevent inconsistent planning classifications
• Quality-control logs record corrections, unresolved issues and data acceptance decisions

Participants can create planning maps that communicate spatial evidence accurately and clearly.

• Map purpose and audience determine scale, extent, hierarchy and annotation
• Visual variables encode nominal, ordinal and quantitative planning data correctly
• Classification methods compared using equal interval, quantile and natural breaks
• Colour schemes selected for accessibility, print reproduction and policy interpretation
• Reference layers, labels, legends and north arrows designed for decision use
• Map layouts include sources, dates, projection, limitations and responsible unit

Participants can use vector geoprocessing methods to answer urban planning questions.

• Buffer analysis measures influence zones around roads, facilities and hazards
• Intersect, union and erase operations combine planning constraints and opportunities
• Spatial joins summarise population, assets and incidents by administrative area
• Point-in-polygon methods assign addresses and facilities to planning zones
• Dissolve operations aggregate parcels and service areas using specified attributes
• Analysis outputs checked for boundary effects, duplicates and invalid geometries

Participants can calculate spatial indicators for population needs and service provision.

• Census indicators joined to enumeration areas using documented geographic identifiers
• Rates and ratios normalised by population, households, area or target group
• Choropleth maps distinguish counts from rates and avoid misleading comparisons
• Dasymetric mapping improves population allocation using buildings and land cover
• Service-area indicators identify underserved settlements and unequal facility distribution
• Modifiable areal unit problem considered when interpreting neighbourhood statistics

Participants can model travel-based access to urban services using network analysis.

• Network datasets represent streets, paths, restrictions, speeds and turn costs
• Service areas calculate reachable populations within time and distance thresholds
• Origin-destination cost matrices compare demand locations with candidate facilities
• Shortest-path analysis identifies efficient routes for emergency and field services
• Walking, transit and driving assumptions tested against local operating conditions
• Accessibility findings translated into facility location and transport recommendations

Participants can build and document a weighted suitability model for an urban site decision.

• Suitability criteria derived from policy, engineering, environmental and community requirements
• Constraints separated from factors before generating candidate development areas
• Raster reclassification converts criteria values into comparable suitability scores
• Weighted linear combination applies documented scores and criterion weights
• Analytic Hierarchy Process supports pairwise comparison of competing criteria
• Sensitivity analysis tests how weight changes affect priority locations

Participants can establish the data model, map extent and initial analysis for their planning project.

• Project charter defines decision question, users, outputs, scope and acceptance criteria
• Study-area boundaries selected using administrative, functional and environmental evidence
• Geodatabase schema configured for project layers, fields, domains and metadata
• Base maps assembled from verified boundaries, roads, parcels and imagery
• Initial spatial indicators calculated for the selected planning problem
• Assumptions register records data gaps, proxies, risks and mitigation actions

Participants can select remotely sensed data appropriate to urban planning and monitoring questions.

• Electromagnetic spectrum bands related to built surfaces, vegetation, water and soil
• Spatial, spectral, temporal and radiometric resolution compared for urban tasks
• Landsat, Sentinel-2 and commercial imagery matched to planning requirements
• Passive optical and active radar sensors distinguished by acquisition conditions
• Pixel values, digital numbers, reflectance and band combinations interpreted correctly
• Image acquisition dates assessed against seasonality, cloud and project timeframes

Participants can prepare satellite imagery for reliable visual interpretation and classification.

• Surface reflectance products selected to reduce atmospheric correction requirements
• Cloud, shadow and no-data masks applied before urban image analysis
• Image mosaics prepared with consistent projection, resolution and acquisition period
• Band composites reveal vegetation, impervious surfaces, water and bare ground
• Normalized Difference Vegetation Index measures vegetation condition and distribution
• Pan-sharpening and resampling assessed for visual detail and analytical limitations

Participants can classify urban land cover and evaluate classification reliability.

• Classification schema defines mutually exclusive land-cover classes and class definitions
• Training samples collected using imagery interpretation and verified reference data
• Supervised classification compares maximum likelihood and random forest approaches
• Object-based image analysis groups pixels using shape, texture and context
• Confusion matrices calculate producer, user and overall accuracy metrics
• Error patterns investigated before publishing land-cover planning interpretations

Participants can measure and explain land-use and land-cover change from multi-date imagery.

• Multi-date imagery aligned by projection, extent, resolution and seasonal conditions
• Post-classification comparison quantifies transitions between land-cover categories
• Change matrices identify conversion from vegetation, agriculture and water to built land
• Image differencing highlights substantial spectral change requiring interpretation
• Urban expansion metrics measure area, edge growth and fragmented development
• Change findings linked to zoning, infrastructure investment and environmental pressures

Participants can use elevation data to assess terrain constraints and flood exposure.

• Digital elevation models assessed for resolution, vertical accuracy and artefacts
• Slope, aspect and hillshade derived for development feasibility assessment
• Fill sinks, flow direction and flow accumulation model drainage pathways
• Watershed delineation identifies upstream catchments affecting urban drainage
• Flood-exposure overlays combine terrain, drainage, buildings, roads and population
• Terrain limitations documented alongside engineering studies and local flood evidence

Participants can map environmental conditions and spatial risk indicators for urban management.

• Urban heat indicators derived from land surface temperature and imperviousness
• Green-space accessibility assessed using walking catchments and population distribution
• Environmental buffers applied around waterways, wetlands and protected areas
• Exposure, sensitivity and adaptive capacity structured within risk assessment
• Hazard maps communicate uncertainty, return periods and intended decision use
• Cumulative impacts screened through overlays of pollution sources and receptors

Participants can plan participatory mapping that incorporates local knowledge responsibly.

• Participatory mapping objectives distinguish validation, co-design, reporting and advocacy uses
• Community sketch maps translated into structured spatial features and attributes
• Focus-group observations coded by location, theme, source and confidence level
• Sensitive locations protected through aggregation, access controls and publication rules
• Ground-truthing protocols compare mapped features with field observations systematically
• Stakeholder feedback incorporated without obscuring authoritative source distinctions

Participants can specify web-based spatial outputs for planners, managers and public users.

• Web map audiences determine layers, scale ranges, pop-ups and search functions
• Operational dashboards display planning indicators, trends, filters and alert thresholds
• Story maps sequence evidence, maps, photographs and recommendations for public review
• Web performance improved through tiled services, scale dependencies and generalisation
• Accessibility requirements address colour contrast, keyboard access and alternative text
• Publication checklists confirm permissions, privacy, metadata and update responsibilities

Participants can define governance controls for sustainable urban GIS operations.

• Data stewardship assigns ownership, maintenance duties, approvals and service levels
• ISO 19115 metadata supports discovery, lineage, quality and reuse decisions
• OGC web service standards support controlled data sharing between systems
• Versioning procedures manage concurrent edits to parcels, assets and zoning layers
• Role-based access controls protect sensitive infrastructure and personal location data
• Implementation roadmaps prioritise datasets, skills, software, governance and measurable benefits

Participants can build, review and present a complete GIS and remote-sensing planning analysis with recommendations.

• Planning problem translated into a reproducible geospatial analysis workflow
• Project geodatabase, metadata and quality checks assembled for technical review
• Vector analysis and imagery evidence integrated into a justified planning finding
• Suitability, accessibility, change or exposure results tested against stated assumptions
• Decision-ready map series prepared with methods, limitations and source documentation
• Stakeholder presentation defends recommendations, uncertainties and implementation priorities