GIS for Decision Support and Planning Training Course

Participants can organise planning data using a documented and governed data model.

• Entity-relationship models define parcels, assets, services, people and administrative areas
• Data dictionaries specify field names, domains, formats, ownership and update cycles
• Metadata records lineage, scale, positional accuracy, restrictions and intended use
• ISO 19115 metadata elements applied to planning and monitoring datasets
• Data governance roles assign stewardship, approval, publication and archival responsibilities
• Privacy controls protect personally identifiable location data and sensitive facilities

Participants can select, check and transform coordinate reference systems for analysis.

• Geographic and projected coordinate systems compared for planning measurements
• Datum differences identified before combining agency, survey and satellite datasets
• EPSG codes used to document coordinate reference system choices
• Projection selection considers area, distance, direction and local distortion
• On-the-fly projection distinguished from permanent dataset reprojection
• Coordinate transformations checked using control points and known feature locations

Participants can prepare reliable integrated datasets for GIS decision support.

• Authoritative sources assessed against volunteered, commercial and open geospatial data
• Tabular records joined using stable identifiers, geocodes and controlled lookup tables
• Geocoding workflows standardise addresses, match scores and exception handling
• Topology rules identify gaps, overlaps, slivers and disconnected network features
• Attribute validation detects duplicates, null values, invalid codes and outliers
• Conflation methods reconcile overlapping roads, facilities and administrative boundary datasets

Participants can use geoprocessing tools to answer defined planning questions.

• Selection by location identifies assets within zones, buffers and administrative areas
• Buffer analysis applies fixed, variable and regulatory setback distances
• Overlay operations compare intersect, union, erase and identity outputs
• Dissolve and aggregation create reporting zones from lower-level spatial units
• Spatial joins summarise counts, rates and attributes by planning area
• ModelBuilder-style workflows document tool parameters, inputs, outputs and dependencies

Participants can select appropriate imagery and derived products for planning questions.

• Optical, radar and thermal imagery matched to planning information requirements
• Spatial, spectral, temporal and radiometric resolution compared before image selection
• Landsat and Sentinel missions assessed for land monitoring applications
• Cloud cover, seasonality and acquisition dates screened for usable observations
• Image metadata reviewed for processing level, projection and quality indicators
• Ground reference data planned to support imagery interpretation and validation

Participants can derive and assess land-cover information from satellite imagery.

• Visual interpretation uses tone, texture, pattern, shape and context
• Spectral indices calculate NDVI, NDBI and NDWI for planning indicators
• Supervised classification uses labelled training samples and class definitions
• Unsupervised clustering groups pixels before analyst interpretation and recoding
• Confusion matrices report producer accuracy, user accuracy and overall accuracy
• Classification outputs converted into planning categories with documented assumptions

Participants can identify, validate and communicate spatial change over time.

• Image-to-image comparison controls season, resolution and registration differences
• Post-classification comparison quantifies land-cover transitions between reporting periods
• Change matrices identify conversion hotspots and persistent land-use patterns
• Time-series charts connect observed change with policy, projects and events
• Threshold methods distinguish meaningful change from noise and classification error
• Monitoring indicators link mapped change to targets, baselines and reporting periods

Participants can design maps that communicate planning evidence accurately and clearly.

• Map purpose determines scale, projection, classification and visual hierarchy
• Sequential, diverging and categorical colour schemes matched to data meaning
• Jenks, quantile and equal-interval classification compared for thematic maps
• Labels, legends and annotation designed for rapid executive interpretation
• Uncertainty and data limitations disclosed through notes, symbology and metadata
• Print and screen layouts checked for accessibility, readability and audience needs

Participants can build transparent site-selection models from multiple spatial criteria.

• Suitability criteria derived from policy requirements, operational needs and constraints
• Exclusion masks remove prohibited, hazardous and infeasible candidate locations
• Raster reclassification standardises criteria onto a common suitability scale
• Weighted overlay combines accessibility, demand, cost, risk and environmental factors
• Boolean logic distinguishes mandatory conditions from preference-based criteria
• Candidate sites ranked with traceable scores, assumptions and sensitivity notes

Participants can apply MCDA methods and test the effect of stakeholder priorities.

• Analytic Hierarchy Process structures criteria, subcriteria and pairwise comparisons
• Pairwise comparison matrices calculate relative weights and consistency ratios
• Stakeholder workshops elicit preferences without confusing values and evidence
• Standardisation methods align indicators measured in different units and ranges
• Sensitivity analysis tests ranking stability under alternative criterion weights
• Trade-off matrices explain competing objectives to decision authorities

Participants can assess travel access, service coverage and network-based gaps.

• Network datasets represent roads, paths, restrictions, turn costs and impedance
• Service areas calculate reachability within defined time, distance and cost thresholds
• Origin-destination cost matrices compare demand locations with service facilities
• Shortest-path analysis identifies efficient routes for inspections and response
• Location-allocation models test facility placement against demand and capacity
• Accessibility indicators reveal underserved populations and priority intervention areas

Participants can identify spatial patterns without confusing random variation and clusters.

• Spatial autocorrelation tests whether observed values cluster beyond random expectation
• Global Moran's I measures overall spatial pattern across reporting areas
• Local Indicators of Spatial Association identify cluster and outlier locations
• Getis-Ord Gi* detects statistically significant hot and cold spots
• Rate normalisation avoids misleading comparisons between unequal population areas
• Modifiable areal unit effects considered before interpreting administrative statistics

Participants can combine hazard, exposure and vulnerability data into planning risk evidence.

• Risk models distinguish hazard probability, exposure and vulnerability components
• Flood, landslide and wildfire layers assessed for source quality and resolution
• Exposure analysis intersects hazards with people, assets, facilities and infrastructure
• Vulnerability indicators combine social, physical and service-access variables
• Scenario maps compare current exposure with proposed development alternatives
• Risk registers connect mapped findings with mitigation actions and responsible owners

Participants can structure repeatable GIS workflows for routine planning analysis.

• Batch processing applies identical geoprocessing steps across multiple administrative units
• Processing models parameterise inputs, thresholds, outputs and validation checks
• Python scripting concepts automate repetitive GIS tasks and file management
• Versioned folders preserve source data, intermediate outputs and final products
• Naming conventions identify geography, date, version, status and responsible analyst
• Quality assurance checklists verify geometry, attributes, calculations and map exports

Participants can specify web-based GIS products for operational and executive users.

• Web map requirements define users, decisions, update frequency and access permissions
• OGC Web Map Service and Web Feature Service support data publication
• Dashboard indicators connect spatial patterns with targets, trends and operational actions
• Filters, pop-ups and layer controls support focused user interrogation
• Role-based access protects restricted assets, personal data and internal planning scenarios
• Performance planning considers caching, generalisation, scale ranges and mobile access

Participants can present GIS findings with clear assumptions, options and recommendations.

• Decision briefs state the question, evidence, findings, options and recommendation
• Map narratives connect spatial patterns with operational consequences and policy choices
• Assumption logs record criteria, weights, exclusions, uncertainties and data gaps
• Stakeholder review protocols test usability, relevance, fairness and implementation feasibility
• Technical appendices provide methods, metadata, validation results and source references
• Recommendations distinguish evidence-supported actions from issues requiring further investigation

Participants can build, review and present a complete GIS decision-support package for a defined planning problem.

• Project charter defines decision owner, planning question, scope and intended users
• Data inventory documents sources, quality checks, restrictions and metadata requirements
• Analysis workflow combines spatial queries, criteria models and validated outputs
• Suitability or prioritisation model records weights, thresholds and sensitivity results
• Decision map package presents findings, limitations, options and recommended actions
• Peer review tests analytical validity, cartographic clarity and decision usefulness