GIS for Real Estate Analysis Training Course

Participants can select appropriate spatial data structures, coordinate systems and geographic reference units.

• Vector, raster and tabular data structures used in property analysis
• Coordinate reference systems, map projections, datums and measurement units
• Parcel polygons, building footprints, points and network datasets compared
• Geographic identifiers linking asset registers, transactions and spatial features
• Scale, resolution and positional accuracy implications for property decisions
• Metadata fields recording source, date, licence, accuracy and update cycle

Participants can evaluate property data sources and establish practical data governance controls.

• Public cadastre, planning, census and transport data source assessment
• Commercial property datasets for transactions, rents, listings and occupiers
• Data licences, permitted uses and restrictions for client reporting
• Source lineage documented from acquisition through analytical output
• Data dictionary fields for assets, parcels, tenancies and market indicators
• Quality controls for completeness, timeliness, consistency and duplication

Participants can create a geodatabase structure that connects property records with spatial features.

• Feature classes, attribute tables and relationship classes for property records
• Parcel-to-asset relationships where ownership and occupation differ
• Unique identifiers supporting joins between GIS and property systems
• Domain values standardising asset type, tenure, status and condition
• Geodatabase schema designed for repeatable property market analysis
• Validation rules preventing invalid dates, areas and property classifications

Participants can geocode property records, resolve exceptions and report matching quality.

• Address standardisation using locality, postal code and street components
• Geocoding workflows for property registers, comparables and competitor locations
• Match scores, candidate review and unmatched address exception handling
• Parcel centroid, rooftop and street interpolation geocoding accuracy compared
• Duplicate detection using address keys, coordinates and property identifiers
• Geocoding quality report covering match rate, errors and residual risks

Participants can produce clear property maps that communicate evidence without distorting interpretation.

• Map purpose determines extent, scale, symbology and level of detail
• Choropleth classification using quantile, equal interval and natural breaks
• Graduated symbols showing rents, values, transactions and unit counts
• Labels, annotation and visual hierarchy for parcel-level property maps
• Basemap selection balancing context, readability, licensing and disclosure
• Map layout standards for investment papers and property reports

Participants can identify and filter property opportunities using spatial and attribute queries.

• Attribute queries filtering assets by area, tenure, value and status
• Spatial selection identifying parcels within designated planning zones
• Intersect operations finding properties affected by constraint boundaries
• Dissolve and merge operations preparing market-area and land assemblage layers
• Area calculations checked against recorded parcel and building measurements
• Screening outputs documented with query logic and exclusion reasons

Participants can measure proximity and access relationships relevant to property value and demand.

• Euclidean buffers measuring proximity to amenities, hazards and competitors
• Distance bands applied to schools, stations, hospitals and retail anchors
• Nearest-feature analysis identifying closest comparable, competitor or transport stop
• Network distance compared with straight-line distance for site assessments
• Accessibility indicators combining travel time, frequency and service coverage
• Buffer assumptions tested against market behaviour and planning guidance

Participants can construct and interpret drive-time, walk-time and customer catchment areas.

• Network analyst settings for walking, driving and service-area calculations
• Drive-time polygons created for retail, healthcare and logistics locations
• Isochrones adjusted for one-way streets, turn restrictions and travel speeds
• Primary, secondary and tertiary trade areas defined from customer behaviour
• Population and household counts summarised within catchment boundaries
• Catchment overlap assessed between proposed and existing trading locations

Participants can combine demographic indicators with location data to estimate local demand.

• Census geographies matched to catchments, neighbourhoods and market areas
• Population density, household income and age profiles mapped appropriately
• Dasymetric mapping improves demand estimates beyond administrative boundary averages
• Household expenditure proxies used cautiously for retail demand analysis
• Demand indicators normalised by population, households or floor area
• Small-area data suppression and confidentiality risks managed in reporting

Participants can map transaction and comparable evidence to identify local market patterns.

• Comparable transaction records cleaned for date, property type and unit basis
• Price per square metre calculated with consistent area definitions
• Temporal filters separating current evidence from obsolete market transactions
• Spatial clustering reveals concentrations of sales, listings and rental activity
• Comparable selection considers proximity, specification, tenure and transaction date
• Market maps distinguish observed evidence from analyst interpretation clearly

Participants can build a transparent multi-criteria suitability model for candidate sites.

• Suitability criteria separated into opportunities, constraints and mandatory exclusions
• Weighted overlay combines standardised scores from multiple spatial criteria
• Reclassification converts raw distances and values into comparable suitability scores
• Analytic Hierarchy Process supports pairwise comparison of selection criteria
• Constraint masks remove protected, restricted and physically unsuitable land
• Sensitivity testing examines how changing weights affects site rankings

Participants can assess development opportunities against planning, legal and physical constraints.

• Zoning, land-use designations and development control layers interpreted carefully
• Setbacks, height limits and density controls mapped for development parcels
• Flood zones, contamination records and protected areas screened spatially
• Easements, rights-of-way and utility corridors identified within site boundaries
• Planning policy dates and authoritative sources recorded for due diligence
• Constraint maps distinguish preliminary screening from formal legal advice

Participants can use imagery and raster data to derive property-relevant site observations.

• Aerial imagery assessed for recency, resolution, seasonality and positional accuracy
• Satellite imagery supports land-cover, growth and site-condition observation
• Raster classification distinguishes built-up land, vegetation, water and bare ground
• Change detection identifies construction progress and land-use conversion
• Digital elevation models indicate slope, drainage and visibility conditions
• Image interpretation findings verified against ground evidence and source dates

Participants can apply basic spatial statistics to interpret clustering, outliers and local variation.

• Spatial autocorrelation tests whether nearby property observations resemble each other
• Moran's I interpretation for prices, rents and vacancy indicators
• Hot Spot Analysis identifies statistically significant market activity concentrations
• Local outlier analysis flags unusual values requiring data or market review
• Kernel density estimation maps transaction and amenity concentration patterns
• Statistical outputs interpreted with sample size and data-quality limitations

Participants can map portfolio composition, concentration and exposure to location-based risk.

• Portfolio geocoding links asset registers to parcels and building locations
• Asset concentration mapped by geography, sector, tenant and value
• Exposure overlays identify flood, transport, planning and regulatory risk
• Vacancy, lease expiry and capital expenditure mapped by asset cluster
• Portfolio dashboards summarise location metrics for management review
• Risk scoring separates observed exposure from management risk appetite

Participants can design repeatable GIS workflows for recurring property analysis and reporting.

• ModelBuilder or graphical workflows document repeatable geoprocessing sequences
• Batch processing updates buffers, joins and map outputs efficiently
• Parameterised models support different markets, sites and reporting periods
• Workflow documentation records inputs, assumptions, outputs and quality checks
• File naming and folder structures support auditability and team handover
• Automation boundaries identified where professional judgement remains essential

Participants can prepare web maps and decision materials for non-technical property stakeholders.

• Web map layers organised for performance, permissions and user interpretation
• Pop-ups present property attributes, comparables and site-screening results
• Interactive filters support review by asset type, market and status
• Executive map narratives link spatial findings to investment decisions
• Uncertainty, data gaps and assumptions disclosed in decision materials
• Map exports formatted for investment committees and due diligence reports

Participants can review GIS analysis for technical accuracy, evidence quality and decision readiness.

• Quality assurance checklist covers geometry, attributes, queries and map outputs
• Topology checks identify gaps, overlaps and invalid parcel boundaries
• Peer review tests criteria, weights, sources and interpretation logic
• Reproducibility checks confirm outputs from documented inputs and procedures
• Version control records data refreshes, model changes and approval status
• Decision-readiness review distinguishes preliminary analysis from formal due diligence

Participants can build, review and present a complete GIS-based real estate location recommendation supported by documented evidence.

• Business brief defines property objective, decision criteria and stakeholder requirements
• Project geodatabase integrates parcels, market indicators, constraints and accessibility data
• Candidate sites screened through queries, catchments and suitability modelling
• Comparable, demographic and competition evidence supports site ranking conclusions
• Quality review documents data limitations, sensitivity findings and residual risks
• Decision presentation communicates recommendation, maps, assumptions and next actions