GIS for Trade and Investment Planning Training Course

Participants can structure planning data and select appropriate spatial reference systems.

• Vector, raster and tabular data structures for location intelligence projects
• Feature classes, attributes, identifiers and relational joins designed purposefully
• Coordinate reference systems selected for distance, area and mapping accuracy
• Projected and geographic coordinate systems compared using planning examples
• Geodatabases organised around assets, markets, constraints and investment sites
• ISO 19115 metadata elements recorded for critical source datasets
• Naming conventions and folder structures supporting reproducible project work

Participants can source, assess and prepare datasets for reliable spatial analysis.

• OpenStreetMap, national statistics and customs sources assessed for fitness
• Data quality dimensions measured through completeness, accuracy, currency and consistency
• Cleaning location fields, duplicates and missing attributes before spatial processing
• Geocoding investor records, warehouses and market addresses using reference data
• Attribute standardisation across currencies, units, dates and administrative codes
• Source provenance documented through metadata, citations and update schedules
• Privacy controls applied to commercially sensitive investor and customer records

Participants can create accurate thematic maps and answer basic spatial questions.

• Layer symbology selected for categorical, sequential and diverging data values
• Choropleth classification using quantiles, natural breaks and equal intervals
• Spatial queries identify facilities within zones, corridors and administrative boundaries
• Buffer analysis measures proximity to ports, borders, airports and utilities
• Spatial joins aggregate establishments, population and investment values by area
• Map layouts include legends, scale bars, sources and decision annotations
• Visual hierarchy applied to distinguish evidence, assumptions and recommendations

Participants can analyse transport access and identify constraints along trade corridors.

• Network datasets model roads, railways, ports, airports and border crossings
• Travel-time surfaces estimate access to gateways and strategic markets
• Origin-destination matrices compare freight routes, costs and journey times
• Isochrones define service areas around logistics hubs and industrial zones
• Corridor bottlenecks identified from travel times, crossings and infrastructure gaps
• Last-mile access assessed between production sites and transport networks
• Accessibility indicators mapped for export-oriented firms and investment zones

Participants can estimate accessible demand and compare market catchments spatially.

• Market potential indices combine population, income, demand and travel impedance
• Catchment areas derived from drive times, distance bands and barriers
• Gravity models estimate market interaction between origins and destinations
• Customer locations analysed for concentration, coverage and service gaps
• Retail and service competition mapped using points of interest
• Trade-area overlap measured to identify cannibalisation and underserved markets
• Demand estimates documented with assumptions, sources and uncertainty ranges

Participants can map industrial ecosystems and identify investment attraction opportunities.

• Industrial clusters mapped from establishment, employment and supplier location data
• Location quotients identify specialised sectors within subnational economic areas
• Supplier proximity assessed through distance matrices and network accessibility
• Anchor firms, logistics assets and skills institutions represented spatially
• Value-chain nodes connected across production, processing and export locations
• Cluster gaps identified through missing services, suppliers and infrastructure
• Investment propositions linked to mapped sector assets and constraints

Participants can select and interpret satellite imagery for trade and investment questions.

• Sentinel-2 and Landsat imagery selected by resolution, revisit and spectral bands
• Spectral signatures distinguish vegetation, water, built surfaces and bare soil
• False-colour composites reveal land cover patterns and surface conditions
• Cloud masking and image compositing improve usable satellite observations
• Spatial resolution matched to industrial estates, roads and agricultural parcels
• Image dates selected to address seasonality, construction cycles and events
• Remote sensing limitations documented alongside ground-truthing requirements

Participants can identify land-use change relevant to site screening and investment monitoring.

• Supervised classification separates built-up land, agriculture, water and vegetation
• Training samples selected from verified imagery and local reference information
• Normalized Difference Vegetation Index indicates vegetation condition and change
• Post-classification comparison identifies conversion, expansion and land disturbance
• Construction activity detected through temporal imagery comparison and interpretation
• Land availability screens exclude protected areas, water bodies and steep terrain
• Accuracy assessment uses confusion matrices, reference samples and error reporting

Participants can build transparent multi-criteria models for site selection.

• Suitability criteria defined from investor requirements and policy constraints
• Hard constraints exclude protected land, hazards and incompatible zoning
• Weighted overlay combines access, labour, utilities, land and market criteria
• Analytic Hierarchy Process compares criterion importance through pairwise scoring
• Raster reclassification converts diverse indicators into common suitability scales
• Sensitivity analysis tests ranking changes under alternative weights
• Candidate sites ranked with documented assumptions and decision rules

Participants can incorporate physical, regulatory and environmental risks into location decisions.

• Flood, drought, wildfire and seismic hazard layers screened for site exposure
• Environmental protected areas and buffer zones incorporated into feasibility analysis
• Climate projections interpreted cautiously for long-term infrastructure and investment decisions
• Multi-hazard overlays identify compound risks affecting industrial and logistics sites
• Critical infrastructure dependencies mapped for power, water and telecommunications resilience
• Regulatory constraints recorded from zoning, permits and environmental requirements
• Risk registers link spatial exposure, likelihood, consequences and mitigation actions

Participants can test whether investment and economic activity patterns are spatially significant.

• Spatial autocorrelation tested using Global Moran's I statistics
• Hot Spot Analysis identifies statistically significant investment and employment concentrations
• Kernel density estimation maps concentrations of firms, transactions and facilities
• Outlier analysis highlights underperforming areas beside high-growth clusters
• Modifiable areal unit problem considered when comparing administrative indicators
• Rate standardisation avoids misleading comparisons between differently sized populations
• Statistical outputs interpreted with confidence levels and operational context

Participants can compare facility and service location scenarios using network-based methods.

• Location-allocation models position facilities against demand points and travel costs
• Maximal coverage models select sites serving the largest reachable population
• P-median models minimise weighted travel distances across demand locations
• Scenario parameters test new roads, borders, hubs and demand growth
• Facility capacity constraints incorporated into service and distribution models
• Equity indicators compare access outcomes across regions and population groups
• Scenario results translated into investment priorities and implementation sequencing

Participants can communicate geospatial findings through decision-ready maps and briefs.

• Executive map design prioritises the decision, evidence and recommended action
• Story maps sequence location context, analysis, findings and investment proposition
• Dashboards combine key indicators, filters, maps and investment opportunity summaries
• Uncertainty statements explain data gaps, model assumptions and confidence limits
• Map annotation clarifies sites, corridors, constraints and critical comparisons
• Technical appendices document methods, data sources and reproducible calculations
• Briefing structures address investor questions, public value and implementation risks

Participants can plan a sustainable GIS workflow for trade and investment functions.

• Data governance roles assign ownership, stewardship, approval and publication responsibilities
• Update cycles defined for infrastructure, firms, trade indicators and imagery
• Quality assurance checklists control geometry, attributes, projections and metadata
• Web GIS publishing permissions protect restricted investor and commercial information
• Interoperability requirements address formats, APIs, identifiers and data exchange
• Standard operating procedures document repeatable analysis and map-production workflows
• Implementation roadmaps specify priorities, skills, tools, budgets and milestones

Participants can build, review and present a complete GIS-based trade or investment planning recommendation.

• Decision brief defines client question, geography, stakeholders and success criteria
• Data inventory documents sources, quality limitations, metadata and update responsibilities
• Analytical workflow integrates accessibility, market, risk and suitability evidence
• Candidate locations compared through weighted criteria and sensitivity testing
• Investment opportunity map communicates assets, constraints and priority actions
• Peer review tests assumptions, evidence quality, map clarity and recommendations
• Final presentation defends findings, implementation steps and governance requirements