GIS Mapping and Spatial Analysis for Monitoring and Evaluation Training Course

Participants can set up GIS projects and inspect the spatial data structures used in M&E work.

• Coordinate reference systems: geographic coordinates, projected coordinates, datums, and transformations
• Choose projected coordinate systems appropriate for distance and area measurement
• Inspect vector attribute tables, field types, joins, and unique identifiers
• Raster cell size, extent, bands, and NoData values
• Set project folders, naming conventions, and reproducible geodatabase structures
• Use QGIS interfaces, layers panel, processing toolbox, and map canvas
• Check layer extent and coordinate reference system before analysis

Participants can source, assess and document spatial datasets for M&E analysis.

• Identify authoritative boundary, population, facility, road, and hazard datasets
• Assess data licences, update dates, lineage, scale, and positional accuracy
• Query HDX, national portals, OpenStreetMap, and agency data catalogues
• Prepare data request specifications for partners and government custodians
• Record source metadata using ISO 19115 core elements
• Compare census, WorldPop, and gridded population denominator options
• Screen humanitarian datasets for access restrictions and sensitivity classifications

Participants can design and quality-check georeferenced field data collection processes.

• Design KoboToolbox forms with geopoints, constraints, skip logic, and required fields
• Configure GPS accuracy thresholds, capture methods, and enumerator guidance
• Code location identifiers linking household records to administrative units
• Validate coordinates against plausible ranges, boundaries, and settlement locations
• Plan offline collection, synchronization, device security, and consent procedures
• Apply informed consent language for collecting location and respondent data
• Reconcile duplicate records, missing coordinates, and conflicting location names

Participants can prepare consistent, linked datasets for spatial monitoring and analysis.

• Standardize place names using gazetteers, controlled vocabularies, and matching rules
• Geocode facilities and events, recording match confidence and source evidence
• Join monitoring tables to geographic layers through stable unique keys
• Reshape indicator data between wide, long, and panel structures
• Create data dictionaries for fields, codes, units, and missing values
• Audit completeness, timeliness, consistency, and validity before spatial processing
• Maintain version logs for corrected datasets and derived outputs

Participants can use vector geoprocessing to analyse service areas, population coverage and gaps.

• Calculate areas, lengths, centroids, and proximity using projected coordinate systems
• Build buffers around clinics, water points, roads, and protected areas
• Clip, intersect, dissolve, and spatially join operational datasets
• Aggregate household observations to wards, districts, and programme catchments
• Use select-by-location queries to identify populations within service zones
• Calculate coverage ratios with population denominators and facility capacities
• Document processing parameters for repeatable indicator production

Participants can produce clear thematic maps for technical, management and community audiences.

• Apply visual hierarchy, figure-ground, alignment, and contrast in thematic maps
• Select nominal, ordinal, interval, and ratio symbology appropriately
• Classify choropleths with quantiles, natural breaks, equal intervals, and thresholds
• Use colourblind-safe palettes and accessible labels for decision audiences
• Construct map layouts with titles, legends, scale bars, north arrows, sources
• Add uncertainty notes where data quality or denominators constrain interpretation
• Export print and web maps at appropriate resolution and format

Participants can map baseline conditions and compare indicator patterns across programme areas.

• Map baseline distributions for access, utilization, outcomes, and vulnerability indicators
• Calculate rates, percentages, prevalence, and incidence using defensible denominators
• Compare indicator values across administrative units without misleading raw counts
• Profile target areas using demographic, service, hazard, and market layers
• Identify baseline outliers requiring data verification or contextual explanation
• Create baseline map series aligned to results framework indicators
• Write map annotations that distinguish observation, interpretation, and recommendation

Participants can assess who is reached, who is missed and where services overlap.

• Define service catchments using administrative rules, travel time, and referral patterns
• Estimate population coverage through buffers, Thiessen polygons, and raster surfaces
• Overlay vulnerability criteria to prioritize communities for programme outreach
• Compare planned beneficiary locations against existing service provider footprints
• Identify geographic gaps, duplication risks, and underserved population clusters
• Use location-allocation concepts for alternative service point placement
• Frame targeting findings with explicit assumptions and exclusion criteria

Participants can estimate physical access to services using distance and travel-time methods.

• Calculate Euclidean distance and explain its operational limitations
• Build travel-time surfaces from roads, land cover, slope, and barriers
• Parameterize walking and vehicle speeds using documented assumptions
• Run least-cost path analysis between communities and health facilities
• Measure facility accessibility against sector-specific service standards
• Compare dry-season and rainy-season accessibility scenarios for contingency planning
• Interpret friction-surface uncertainty in access estimates and decisions

Participants can test and interpret geographic clustering in monitoring and outcome data.

• Distinguish spatial autocorrelation, clustering, dispersion, and random spatial patterns
• Calculate Global Moran's I for area-based monitoring indicators
• Use Local Moran's I to identify high-high and low-low clusters
• Apply Getis-Ord Gi* hotspot analysis with defined distance bands
• Test whether observed patterns exceed chance under spatial randomness assumptions
• Choose spatial weights matrices based on contiguity or distance
• Report statistical significance, multiple-testing limitations, and practical relevance

Participants can use raster data and satellite imagery to strengthen M&E evidence.

• Interpret spectral bands, spatial resolution, temporal resolution, and cloud contamination
• Derive NDVI and normalized difference water index from satellite imagery
• Classify land cover with supervised methods and reference samples
• Use change detection to monitor settlement expansion and vegetation loss
• Assess classification accuracy using confusion matrices and validation points
• Extract zonal statistics for administrative units and programme areas
• Combine raster exposure layers with population grids for risk estimates

Participants can develop operational maps for risk analysis, response planning and coordination.

• Map hazards, exposure, vulnerability, and coping capacity using risk frameworks
• Overlay flood extent, displacement sites, health facilities, and road access
• Produce contingency maps for evacuation routes, staging areas, and access constraints
• Incorporate seasonal calendars into hazard and service availability analysis
• Track incident locations while protecting affected populations and staff
• Use Common Operational Datasets for coordinated humanitarian mapping products
• Set update triggers for rapidly changing displacement and access information

Participants can apply spatial methods to sampling, comparison areas and evaluation interpretation.

• Design spatial sampling frames using clusters, grids, enumeration areas, and strata
• Assess spatial representativeness before generalizing survey findings to programme areas
• Map treatment and comparison areas for quasi-experimental evaluation designs
• Identify spillover, contamination, and displacement risks around intervention boundaries
• Match before-and-after observations using consistent geographic units and identifiers
• Use difference-in-differences maps to communicate geographically varied programme change
• Document boundary changes that compromise longitudinal indicator comparability

Participants can specify and maintain spatial dashboards for recurring monitoring decisions.

• Prepare analysis-ready layers for web maps, dashboards, and scheduled updates
• Design indicator dashboards linking maps, charts, filters, and disaggregations
• Set refresh workflows for routine monitoring data and derived indicators
• Apply role-based access controls to sensitive operational map products
• Specify decision questions before selecting dashboard metrics and map interactions
• Create metadata panels showing source, update date, definitions, and caveats
• Test dashboard outputs against user tasks and bandwidth constraints

Participants can review spatial outputs for quality, privacy, protection and ethical risks.

• Apply positional accuracy, attribute accuracy, completeness, consistency, and currency checks
• Assess spatial bias from uneven reporting, missing data, and access constraints
• Minimize harm through aggregation, masking, jittering, and controlled dissemination
• Conduct data protection impact assessments for sensitive location datasets
• Set retention schedules, access permissions, and secure sharing protocols
• Review maps for stigma, re-identification, political sensitivity, and protection risks
• Use peer review checklists before publishing spatial findings

Participants can communicate geographic findings, limitations and recommendations to decision-makers.

• Structure map-based findings around decision, evidence, uncertainty, and action
• Write analytical captions that state pattern, comparison, and operational implication
• Select map scales appropriate to executive, district, and field audiences
• Build briefing packs combining locator maps, indicator maps, and recommendations
• Present uncertainty using confidence notes, ranges, and data-quality flags
• Distinguish correlation from causation when explaining mapped programme results
• Record management responses and follow-up actions from spatial evidence

Participants can plan GIS workstreams that fit M&E cycles, roles and decision deadlines.

• Define spatial analysis deliverables, users, decisions, data sources, and deadlines
• Develop a GIS analysis plan aligned with M&E workplans
• Sequence data preparation, analysis, quality assurance, review, and publication tasks
• Assign roles using RACI for data custodians, analysts, and approvers
• Estimate effort, software, data acquisition, and field verification requirements
• Specify acceptance criteria for maps, indicators, and dashboard outputs
• Establish change-control procedures for revised boundaries and indicator definitions

Participants can establish repeatable workflows for periodic spatial monitoring and reporting.

• Build processing models that document inputs, parameters, outputs, and dependencies
• Create standardized map templates for recurring monthly and quarterly reports
• Maintain metadata records, code lists, and processing logs for audit trails
• Version spatial datasets using dated releases and controlled editing permissions
• Automate routine joins, calculations, and exports with GIS processing tools
• Schedule quality checks before indicator publication and management review
• Archive final map products with source data and methodological notes

Participants can build, review and present a complete GIS-supported M&E analysis addressing a defined programme decision.

• Define a complete M&E spatial question, indicator specification, and decision user
• Prepare, validate, and integrate monitoring, boundary, population, and contextual datasets
• Apply appropriate vector, raster, accessibility, or clustering analysis methods
• Produce decision-ready maps with metadata, uncertainty notes, and protection safeguards
• Review findings against quality, ethics, and results-framework requirements
• Present recommendations, limitations, and an implementation plan to stakeholders