GIS for Housing and Settlement Planning Training Course

Participants can specify the datasets, indicators and collection priorities required for a planning assignment.

• Housing stock indicators: tenure, condition, occupancy and affordability
• Settlement indicators for density, access, services, risk and growth
• Parcel, building, road and utility datasets required for site analysis
• Population grids and census boundaries matched to planning geographies
• Indicator definitions aligned with planning objectives and decision thresholds
• Data collection plans covering sources, frequency, ownership and update responsibility

Participants can create a geodatabase structure that supports housing and settlement analysis.

• Feature classes designed for parcels, buildings, facilities and infrastructure
• Attribute domains standardise housing condition, tenure and service categories
• Relationship classes connect households, structures, parcels and occupancy records
• Unique identifiers prevent duplicate records across survey and administrative sources
• Field naming conventions support reliable joins, queries and data exchange
• Versioned update procedures maintain current settlement and housing inventories

Participants can assess fitness for use and document sensitive settlement data responsibly.

• Positional accuracy assessed against parcel, building and infrastructure requirements
• Completeness checks identify missing attributes, features and survey coverage
• Logical consistency rules detect overlaps, gaps and invalid geometry
• ISO 19115 metadata elements record source, lineage, quality and restrictions
• Household privacy controls limit disclosure of sensitive location information
• Bias assessment identifies undercounting risks within informal settlement datasets

Participants can prepare field data workflows that connect surveys to a settlement geodatabase.

• Mobile survey forms capture household, structure and service observations
• Field validation rules reduce invalid coordinates and incomplete records
• Sampling frames distinguish household surveys from complete structure inventories
• Global Positioning System accuracy considerations for dense built-up areas
• Photo documentation linked to feature identifiers and survey timestamps
• Quality assurance routines reconcile field submissions with existing GIS records

Participants can analyse parcel, tenure and land administration data for housing planning.

• Cadastral parcels linked with tenure, ownership and development status
• Parcel topology checks identify slivers, overlaps and unclosed boundaries
• Land use classifications distinguish residential, mixed-use and restricted areas
• Title, lease and customary tenure records interpreted for planning constraints
• Subdivision patterns reveal fragmented land assembly and servicing challenges
• Query expressions identify vacant, underused and publicly controlled parcels

Participants can select suitable imagery and interpret remote sensing characteristics for settlement studies.

• Spatial, spectral, temporal and radiometric resolution compared for settlement mapping
• Optical imagery limitations under cloud cover, haze and shadow
• Synthetic aperture radar applications for flood-prone and cloudy locations
• Image acquisition dates matched with planning questions and seasonal conditions
• False-colour composites distinguish vegetation, water, roofs and bare ground
• Visual interpretation keys use tone, texture, shape and spatial association

Participants can prepare satellite imagery and derive classified land-cover information.

• Radiometric correction improves comparison between imagery acquired on different dates
• Image mosaicking combines adjacent scenes with consistent colour balancing
• Training samples selected for supervised land-cover classification
• Random forest classification separates built-up land, vegetation and water
• Object-based image analysis groups pixels into meaningful settlement features
• Confusion matrices report producer, user and overall classification accuracy

Participants can derive settlement form indicators from buildings, roads and imagery.

• Building footprint extraction supports structure counts and coverage estimates
• Roof density measures identify compact, dispersed and transitional settlement patterns
• Block morphology reveals permeability, plot access and street connectivity
• Regular grid analysis compares building concentration across neighbourhoods
• Kernel density estimation identifies clusters of structures and activity
• Settlement typologies classify planned, informal, peri-urban and rural areas

Participants can map housing need indicators and identify priority service gaps.

• Housing deficit indicators combine overcrowding, condition and tenure insecurity
• Choropleth mapping compares neighbourhood indicators using appropriate normalisation
• Rate calculations distinguish absolute counts from population-adjusted need
• Bivariate maps show relationships between housing condition and service access
• Spatial joins aggregate household observations to wards and planning zones
• Priority indices rank locations using transparent housing need criteria

Participants can measure access to services using network-based spatial analysis.

• Network datasets model roads, paths, barriers and travel restrictions
• Service areas estimate reachable schools, clinics and water points
• Origin-destination cost matrices compare travel times from settlement blocks
• Walking access thresholds test proximity to public facilities
• Location-allocation models identify candidate sites for new facilities
• Accessibility maps distinguish geographic proximity from usable route access

Participants can construct and test a multi-criteria housing land suitability model.

• Suitability criteria define physical, legal, environmental and service requirements
• Constraint mapping excludes protected land, hazard zones and rights-of-way
• Weighted overlay combines standardised factors using documented relative importance
• Analytic Hierarchy Process compares criteria through pairwise weighting
• Distance rasters measure proximity to roads, utilities and employment centres
• Sensitivity testing examines how weighting changes recommended development areas

Participants can assess infrastructure coverage and identify settlement servicing priorities.

• Utility network layers represent water, sanitation, electricity and drainage assets
• Buffer analysis estimates households within planned service connection distances
• Capacity attributes identify constrained pipes, substations and drainage channels
• Catchment delineation links terrain flow paths with drainage investment planning
• Service gap maps compare infrastructure coverage against population distribution
• Phased infrastructure plans sequence trunk, secondary and household-level investments

Participants can incorporate hazard exposure and environmental constraints into settlement decisions.

• Flood hazard layers combined with buildings, roads and population exposure
• Digital elevation models derive slope, drainage direction and low-lying areas
• Landslide susceptibility factors include slope, geology, vegetation and rainfall
• Heat exposure mapping identifies low-canopy, dense built-up neighbourhoods
• Environmental setback buffers protect waterways, wetlands and conservation areas
• Risk matrices combine hazard likelihood, exposure and vulnerability indicators

Participants can develop spatial evidence for inclusive informal settlement upgrading decisions.

• Participatory mapping incorporates resident knowledge into settlement base maps
• Enumeration data links households, structures, tenure and service conditions
• Access corridors mapped for emergency response and infrastructure installation
• Upgrading zones distinguish improvement, regularisation, relocation and protection options
• Eviction and displacement risks assessed through tenure and hazard evidence
• Community validation procedures correct mapped features and local place names

Participants can measure settlement expansion and establish monitoring indicators.

• Multi-date imagery comparison identifies expansion, densification and land conversion
• Post-classification change detection quantifies transitions between land-cover classes
• Building count trends measure development intensity over defined periods
• Time-series indicators track service delivery, housing condition and risk exposure
• Monitoring baselines establish measurable targets for settlement improvement programmes
• Update schedules align imagery, surveys and administrative records with decisions

Participants can use spatial statistics to interpret patterns without overstating findings.

• Global Moran's I tests overall spatial clustering of housing indicators
• Local Indicators of Spatial Association identify neighbourhood-level priority clusters
• Hot spot analysis highlights statistically significant concentrations of need
• Modifiable areal unit problem considered when selecting reporting boundaries
• Correlation analysis distinguishes association from causal planning explanations
• Indicator dashboards present trends, disaggregation and data quality notes

Participants can produce clear maps and visual products for technical and non-technical audiences.

• Map purpose determines scale, extent, symbology and annotation choices
• Sequential, diverging and categorical colour schemes match data measurement levels
• Classification methods compare equal interval, quantile and natural breaks
• Layout hierarchies organise titles, legends, sources, scale bars and disclaimers
• Uncertainty communicated through notes, confidence classes and careful language
• Web map and dashboard specifications support recurring planning decisions

Participants can prepare an implementation plan for a sustainable settlement GIS function.

• Roles matrix assigns data stewardship, quality control and publication responsibilities
• Standard operating procedures govern editing, validation, approval and archiving
• Data sharing agreements define access, permitted use and confidentiality obligations
• Interoperability planning addresses formats, identifiers, services and update cycles
• Hardware, software and connectivity requirements matched with operational workloads
• Implementation roadmaps sequence quick wins, milestones, resources and risks

Participants can build, review and present a complete GIS analysis package for a housing or settlement planning decision.

• Planning brief defines decision question, users, geography and success criteria
• Source inventory records datasets, quality limitations and data protection controls
• Geodatabase integrates land, housing, population, services and hazard information
• Spatial analysis combines suitability, accessibility, need and risk indicators
• Decision maps present priority areas, scenarios and recommended planning actions
• Technical documentation states methods, assumptions, validation results and limitations