GIS for Sustainable Development Goals Training Course

Participants can define measurable spatial indicators aligned with SDG metadata.

• UN SDG indicator metadata: concepts, definitions, units and disaggregation
• Indicator selection using relevance, feasibility, comparability and actionability criteria
• Proxy indicators where official SDG data are unavailable
• Numerators, denominators and geographic rates for local measurement
• Baseline, target and reporting-period design for mapped indicators
• Documenting assumptions, exclusions and indicator interpretation limits

Participants can establish a structured GIS project for an SDG analysis.

• Vector features, raster cells, attributes and relational data tables
• Geodatabases, folders and naming conventions for reproducible projects
• Layer schemas matching indicator definitions and reporting geography
• Feature identifiers linking spatial layers with statistical records
• Project files, relative paths and portable data-package design
• Data dictionaries recording fields, formats, sources and update schedules

Participants can align and integrate spatial datasets without location errors.

• Geographic and projected coordinate reference systems distinguished correctly
• Datum transformations selected for national and regional datasets
• Geocoding facilities, settlements and programme sites from address records
• Spatial joins connecting population tables to administrative polygons
• Geoprocessing boundaries using clip, dissolve, merge and intersect tools
• Positional error checks before combining datasets from different sources

Participants can source and evaluate data for a defined SDG analysis.

• Official statistics, censuses and household surveys as spatial evidence sources
• OpenStreetMap and government portals for facilities and infrastructure
• Earth observation archives for land, water and settlement indicators
• Administrative boundary sources assessed for currency and authority
• Data licensing, access restrictions and redistribution conditions
• Acquisition log capturing source, date, version and intended use

Participants can assess fitness for purpose and document geospatial datasets.

• Completeness, positional accuracy, attribute accuracy and temporal accuracy measures
• Logical consistency checks for topology, duplicates and invalid values
• Sampling approaches for field verification and accuracy assessment
• ISO 19115 metadata elements for geospatial dataset documentation
• Data lineage records tracing transformations, sources and processing decisions
• Fitness-for-purpose assessment against indicator precision and reporting requirements

Participants can map population needs and inequalities at appropriate scales.

• Population grids, census enumeration areas and administrative population estimates
• Rates, proportions and counts mapped without misleading visual comparisons
• Choropleth classification using quantiles, natural breaks and equal intervals
• Disaggregation by sex, age, disability and urban-rural location
• Modifiable areal unit problem in subnational SDG analysis
• Small-area estimates interpreted with uncertainty and sampling limitations

Participants can measure physical access to services using GIS network methods.

• Euclidean distance surfaces for preliminary facility access screening
• Road-network travel time modelling using speed and impedance assumptions
• Service areas identifying populations within defined travel thresholds
• Catchment areas adjusted for barriers, terrain and transport modes
• Population coverage estimates linked to clinics, schools and water points
• Accessibility results validated against local travel and service conditions

Participants can design a field-data workflow that supports SDG indicators.

• Survey forms structured around indicator variables and controlled vocabularies
• GPS capture settings, accuracy thresholds and waypoint validation
• Required fields, skip logic and range checks in mobile forms
• Field protocols for facilities, water points and community assets
• Synchronisation procedures for offline collection and central quality review
• Consent, safeguarding and privacy controls for household location data

Participants can derive environmental measures from raster data and terrain models.

• Raster resolution, extent, cell size and resampling choices
• Digital elevation models for slope, aspect and drainage analysis
• Raster calculator expressions for environmental indicator derivation
• Zonal statistics summarising raster values by reporting area
• Reclassification rules converting continuous surfaces into policy thresholds
• NoData handling and edge effects in raster calculations

Participants can select suitable satellite imagery for an SDG monitoring question.

• Electromagnetic spectrum bands used for land and water observation
• Spatial, spectral, temporal and radiometric resolution trade-offs
• Sentinel-2 and Landsat imagery for development monitoring
• Cloud cover, seasonal timing and image-selection criteria
• Surface reflectance products and atmospheric correction rationale
• Image catalogues filtered by location, date and quality metadata

Participants can calculate and interpret spectral indices for environmental indicators.

• Normalized Difference Vegetation Index for vegetation condition assessment
• Normalized Difference Water Index for surface-water detection
• Normalized Difference Built-up Index for settlement expansion screening
• Band combinations selected for agriculture, water and urban interpretation
• Threshold selection tested against reference imagery and local knowledge
• Seasonal effects separated from meaningful environmental change

Participants can produce and evaluate a classified land-cover map.

• Supervised classification using labelled training samples and spectral signatures
• Unsupervised clustering for initial land-cover pattern exploration
• Training data selection across representative classes and conditions
• Confusion matrices reporting producer, user and overall accuracy
• Reference samples separated from classifier training observations
• Class definitions aligned with reporting needs and interpretation guidance

Participants can quantify and explain mapped change between reporting periods.

• Post-classification comparison identifying transitions between land-cover classes
• Image differencing for vegetation, water and built-up change
• Time-series charts built from repeated satellite observations
• Change thresholds tested against seasonality, clouds and classification error
• Transition matrices summarising gains, losses and stable areas
• Narrative interpretation linking detected change to programme and policy context

Participants can combine hazard and population data to prioritise risk reduction.

• Hazard layers for floods, droughts, heat and landslides
• Exposure analysis intersecting hazards with population and infrastructure
• Vulnerability proxies using housing, poverty and service-access indicators
• Risk matrices combining likelihood, exposure and consequence scores
• Scenario maps comparing current conditions with future climate assumptions
• Priority areas ranked using transparent multi-criteria decision rules

Participants can identify statistically meaningful geographic clustering in SDG data.

• Spatial autocorrelation measured using Global Moran's I statistic
• Local Indicators of Spatial Association locating clustered values
• Getis-Ord Gi-star hotspot analysis for priority area identification
• Rate smoothing for unstable indicators in small populations
• Spatial weights matrices based on contiguity and distance
• Statistical significance interpreted alongside programme knowledge and data quality

Participants can create maps that communicate SDG findings accurately to decision-makers.

• Map purpose, audience and decision question established before design
• Visual hierarchy using symbol size, colour value and label priority
• Colour schemes selected for sequential, diverging and categorical data
• Legends, scale bars, north arrows and source notes applied
• Uncertainty and data limitations communicated through map annotations
• Briefing notes linking spatial findings to recommended management actions

Participants can package GIS results for repeatable SDG reporting cycles.

• Dashboard indicators connected to maps, charts and filter controls
• Reporting templates aligning geographic evidence with SDG indicator metadata
• ModelBuilder and processing models for repeatable geoprocessing sequences
• Version control principles for datasets, scripts and map outputs
• Quality assurance checklists completed before publication or submission
• Update schedules assigning data owners, review points and release dates

Participants can plan a governed geospatial workflow for an SDG programme.

• Data governance roles for custodianship, approval, access and maintenance
• Privacy impact assessments for personal and sensitive location information
• Data-sharing agreements covering purpose, retention and permitted users
• Interoperability principles for agencies exchanging geospatial SDG datasets
• Implementation roadmaps defining milestones, resources, risks and dependencies
• Capacity plans covering technical roles, training and support arrangements

Participants can build, review and present a complete geospatial evidence package for a defined SDG decision.

• Problem statement linking an SDG target to a management decision
• Indicator specification defining measures, geography, period and disaggregation
• Data inventory documenting sources, quality issues and permissions
• GIS workflow combining spatial analysis, remote sensing and validation
• Map series and dashboard outputs communicating priority findings
• Peer review against accuracy, ethics, metadata and decision usefulness