GIS and Remote Sensing for National Planning Training Course

Participants can design a structured geodatabase for a multi-source planning analysis.

• Vector, raster and tabular models matched to planning information needs
• Feature classes, attribute tables and relationship classes for planning datasets
• Geodatabase schema design using domains, subtypes and unique identifiers
• Administrative boundaries, gazetteers and settlement hierarchies as reference layers
• File geodatabases, GeoPackages and enterprise geodatabase use cases
• Naming conventions and folder structures supporting reproducible GIS projects

Participants can align datasets accurately using appropriate coordinate reference systems and transformations.

• Geographic and projected coordinate reference systems distinguished through map purpose
• Datum transformations selected for national datasets from different sources
• Universal Transverse Mercator zones and national grid system selection
• On-screen coordinate checks for detecting projection and alignment errors
• Georeferencing scanned plans using ground control points and residuals
• Positional accuracy documented before combining layers for planning analysis

Participants can acquire, clean and assess spatial datasets before analysis.

• Open data portals assessed for licence, currency, completeness and authority
• Field, census and administrative records joined through consistent identifiers
• Attribute cleaning rules for missing values, duplicates and invalid codes
• Topology rules detect gaps, overlaps, dangles and boundary inconsistencies
• Data quality dimensions assessed through accuracy, completeness, timeliness and lineage
• ISO 19115 metadata elements recorded for planning datasets and map products

Participants can use vector geoprocessing to quantify spatial relationships and planning constraints.

• Buffer zones applied to roads, rivers, protected areas and facilities
• Overlay operations compare proposed development with regulatory constraint layers
• Intersect, union and erase tools create policy-relevant planning zones
• Spatial joins summarise population and assets within administrative areas
• Dissolve and aggregation methods prepare reporting units for decision-makers
• Query expressions isolate parcels, settlements and facilities meeting criteria

Participants can prepare and analyse raster datasets for terrain and land-surface planning evidence.

• Raster cell size selected according to planning scale and source resolution
• Digital elevation models derive slope, aspect and terrain ruggedness
• Reclassification converts continuous surfaces into policy-relevant suitability classes
• Raster calculator combines standardised criteria using explicit mathematical expressions
• Hydrological tools delineate catchments, flow direction and drainage accumulation
• NoData values managed to prevent misleading surface-analysis results

Participants can interpret sensor characteristics and select imagery suited to planning objectives.

• Electromagnetic spectrum regions linked to vegetation, water and built surfaces
• Spectral signatures explain reflectance differences among common land-cover materials
• Spatial, spectral, temporal and radiometric resolution compared for imagery selection
• Landsat and Sentinel missions matched to monitoring and planning requirements
• Passive and active sensors distinguished through acquisition and interpretation principles
• Cloud cover, seasonality and acquisition dates assessed before image selection

Participants can prepare satellite imagery for consistent visual interpretation and quantitative analysis.

• Image bands stacked, clipped and resampled for defined study areas
• True-colour and false-colour composites selected for target feature identification
• Atmospheric correction concepts considered when comparing multi-date imagery
• Cloud, shadow and haze masks applied before image classification
• Image mosaics balanced across scenes using consistent processing parameters
• Raster statistics and histograms inspected for data-quality anomalies

Participants can produce and evaluate a land-cover classification for planning use.

• Land-cover classification scheme defined from planning questions and available imagery
• Training samples selected using representative spectral and geographic variation
• Supervised classification methods compare maximum likelihood and random forest approaches
• Unsupervised clustering interpreted and labelled using reference data
• Confusion matrices calculate producer, user and overall classification accuracy
• Ground truth, visual interpretation and reference datasets validate classified outputs

Participants can calculate and interpret spectral indices for environmental and settlement planning evidence.

• Normalized Difference Vegetation Index identifies relative vegetation condition and change
• Normalized Difference Water Index highlights surface water and moisture patterns
• Normalized Difference Built-up Index supports settlement expansion assessment
• Index thresholds tested against imagery, field knowledge and seasonal conditions
• Time-series charts compare seasonal variability with persistent land-surface changes
• Indicator limitations documented where mixed pixels distort interpretation

Participants can build a transparent multi-criteria suitability model for a planning decision.

• Planning objectives converted into constraint, factor and preference criteria
• Boolean exclusion masks remove legally unsuitable or hazardous locations
• Standardisation scales convert diverse criteria into comparable suitability scores
• Analytic Hierarchy Process weights derived from pairwise criterion comparisons
• Weighted overlay combines terrain, access, population and environmental factors
• Sensitivity analysis tests how changed weights affect priority locations

Participants can assess access to facilities and identify underserved populations spatially.

• Network datasets model roads, travel restrictions, speeds and connectivity
• Service areas estimate populations within defined travel-time thresholds
• Origin-destination cost matrices compare settlements with candidate facility locations
• Euclidean distance surfaces distinguish straight-line proximity from network access
• Catchment analysis identifies overlapping coverage and service-access gaps
• Accessibility findings disaggregated by administrative area and population group

Participants can identify, quantify and communicate spatial change using multi-date data.

• Post-classification comparison quantifies transitions between land-cover categories
• Image differencing identifies major surface changes between acquisition dates
• Change matrices summarise gains, losses and persistent land-cover classes
• Urban expansion measured against plans, protected land and infrastructure corridors
• Hotspot analysis identifies statistically significant clusters of change observations
• Monitoring indicators linked to baselines, targets and reporting cycles

Participants can produce readable maps and technical messages that support planning decisions.

• Visual hierarchy directs attention to the planning decision and evidence
• Classification methods compare equal interval, quantile and natural breaks
• Colour schemes selected for accessibility, meaning and map reproduction
• Scale bars, legends, north arrows and sources completed accurately
• Map layouts combine analytical outputs, context layers and concise annotations
• Uncertainty statements explain data limitations without obscuring key findings

Participants can establish governance controls for repeatable and accountable planning GIS work.

• Data governance roles assign ownership, custodianship, access and update responsibilities
• Metadata records capture source, method, date, limitations and usage conditions
• Version control practices preserve analysis history and approved data releases
• Standard operating procedures document processing steps and quality checks
• Data-sharing agreements address confidentiality, licences and permitted uses
• Quality assurance checklists support technical review before decision submission

Participants can select appropriate cloud and web GIS approaches for sharing planning evidence.

• Web map design separates operational layers from public communication layers
• Cloud processing concepts compare local workflows with Google Earth Engine
• Tile services and feature services selected according to data-update requirements
• Interactive dashboards combine indicators, maps and planning status information
• User permissions protect sensitive infrastructure and population datasets
• Publication checks verify symbology, scale behaviour and accessible map descriptions

Participants can build, review and present a complete GIS and remote sensing planning analysis for a defined national planning decision.

• Planning brief defines decision, study area, users and success criteria
• Geodatabase integrates authoritative boundaries, imagery, indicators and constraint layers
• Analysis workflow combines classification, accessibility and suitability modelling methods
• Quality review tests projections, attributes, assumptions and output consistency
• Map series communicates evidence, priority areas, limitations and recommended actions
• Technical presentation defends methods, findings and implementation priorities to reviewers