GIS Data Collection and Mapping Training Course

Duration 10 days 18 modules · 65 contact hours
Level Intermediate Certificate on completion
Who attends GIS Analysts, Survey and Field Officers and others
Fee from USD 2,200 KSh 190,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 9 Nov 2026 Course code SD-GRS-027

Before you join: Participants should understand basic map concepts, including points, lines, polygons, layers and attribute tables.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

GIS teams are often asked to turn field observations, asset records, imagery and third-party datasets into maps that support decisions. The difficulty is rarely drawing a map. It is defining fit-for-purpose data, controlling coordinate systems, capturing reliable attributes, checking quality, analysing spatial relationships and presenting findings without overstating certainty. Poorly specified collections, inconsistent fields, incorrect projections and undocumented processing can produce costly operational errors.

This intermediate course develops the practical methods required to plan, collect, clean, analyse and publish GIS data. Participants work with vector and raster data, geodatabases, mobile collection forms, GNSS settings, satellite imagery, spatial queries, buffers, overlays, suitability models and cartographic design. They learn how to apply topology rules, metadata standards, quality checks and data governance controls while producing outputs suitable for asset management, humanitarian operations, environmental monitoring, utilities, land administration and infrastructure planning.

Delivered over 10 instructor-led days in the classroom or live online, the course combines concise technical briefings with case work, group analysis, mapping tasks and structured review. Participants build work from the first week, progressing from a data collection specification to analysis, web-ready map products and documented handover material. They leave with a completed GIS project package containing a data model, collection plan, quality assurance evidence, analysis outputs, map layouts and a presentation-ready decision briefing.

The course suits professionals who already work with maps, location data or operational records and need a disciplined approach to creating reliable GIS products. It is particularly relevant to analysts, survey teams, planners, asset managers, environmental specialists and programme staff who commission or produce spatial data.

What you will be able to do

  • Design a GIS data collection specification with attributes, tolerances and acceptance criteria
  • Configure geodatabases using feature classes, domains, subtypes and relationship classes
  • Apply coordinate reference systems, datum transformations and projection checks correctly
  • Conduct field data collection using mobile forms, GNSS settings and offline map areas
  • Validate vector and attribute data using topology rules, sampling plans and error logs
  • Perform spatial analysis using queries, buffers, overlays, proximity and suitability methods
  • Produce accessible map layouts and web map layers for defined audiences
  • Present a documented GIS project with metadata, quality evidence and decision findings

Benefits of attending

For you

  • Produce field-to-map workflows suitable for professional GIS assignments
  • Diagnose projection, topology and attribute errors before publication
  • Create evidence-based suitability, proximity and change-analysis outputs
  • Build a reusable portfolio project with documented methods and quality checks
  • Communicate spatial findings clearly to technical and non-technical reviewers

For your organisation

  • Improve consistency of field collection forms, attributes and location records
  • Reduce rework caused by invalid geometries, missing metadata and projection errors
  • Create auditable GIS outputs for asset, environmental and programme decisions
  • Shorten production time through reusable processing models and quality checklists
  • Strengthen control of sensitive location data, licences and publication permissions

Course modules

18 modules over 10 days

Participants can convert a business request into a defined GIS data requirement.

  • GIS project questions translated into measurable spatial data requirements
  • Coordinate reference systems, datums and projections distinguished for project use
  • Vector, raster, tabular and metadata structures compared for fitness
  • Data lifecycle mapped from field capture through publication and retention
  • Accuracy, precision, uncertainty and scale assessed before collection begins
  • Project scope documented using purpose, users, geography, time and quality

Participants can configure a geodatabase structure for controlled data capture and maintenance.

  • Geodatabase feature classes, tables, domains and subtypes configured correctly
  • Primary keys and relationship classes model one-to-many asset records
  • Field names, aliases, data types and null rules specified
  • Controlled vocabularies and coded value domains prevent inconsistent entries
  • ISO 19115 metadata elements recorded for datasets and services
  • Versioning and edit permissions assigned for shared authoritative layers

Participants can select, transform and verify coordinate reference systems for GIS projects.

  • CRS selection matched to area, distance, direction and legal reporting
  • On-the-fly projection checked against source metadata and basemap alignment
  • Geographic and projected coordinate systems compared using distortion indicators
  • Transformation methods selected between WGS 84 and local datums
  • GPS coordinates converted between decimal degrees and projected eastings
  • Projection errors diagnosed using control points and known distances

Participants can create a controlled field collection plan and mobile form design.

  • Field collection plan defines features, attributes, tolerances and acceptance rules
  • Sampling designs chosen for inventories, condition surveys and environmental observations
  • Survey123 and QField forms built with required fields and conditional logic
  • GNSS accuracy settings matched to asset, boundary and inspection requirements
  • Photo, audio and document attachments linked to feature records
  • Offline map areas packaged for disconnected field collection

Participants can assess, import and document data from common GIS sources.

  • Satellite, drone, scanned-map and CAD sources assessed before import
  • Delimited text, GeoJSON, Shapefile and GeoPackage files imported safely
  • Schema mapping reconciles supplier fields with target geodatabase specifications
  • Geocoding outputs reviewed using match scores and exception lists
  • Raster band properties inspected before imagery analysis and classification
  • Provenance recorded for source, licence, date, processing and custodian

Participants can test spatial data quality and record corrective actions.

  • Topology rules detect gaps, overlaps, dangles and duplicate geometries
  • Attribute validation identifies missing codes, invalid ranges and date errors
  • Positional accuracy tested against control points and reference imagery
  • Completeness measures compare delivered records with planned collection totals
  • QA sampling plans set inspection rates, thresholds and rework decisions
  • Error logs document defect type, severity, correction and closure

Participants can edit vector layers while preserving geometry and attribute integrity.

  • Snapping, tracing and vertex editing produce clean feature geometry
  • Split, merge, reshape and buffer tools update asset boundaries
  • Field Calculator derives areas, lengths, IDs and status values
  • Spatial joins transfer attributes using containment, intersection and nearest methods
  • Duplicate records resolved through matching keys, geometry and business rules
  • Edit sessions documented with change reasons and source evidence

Participants can answer operational questions using vector-based spatial analysis methods.

  • SQL definition queries isolate records using attributes, dates and coded values
  • Spatial selection identifies features within, intersecting or touching target areas
  • Buffer analysis estimates service catchments, exclusion zones and exposure distances
  • Overlay operations compare land parcels, hazards, facilities and population data
  • Proximity analysis ranks sites using nearest-feature distances and travel constraints
  • Query results validated against maps, totals and original business questions

Participants can prepare and analyse raster data for classification and monitoring.

  • Raster resolution, extent, bands and bit depth determine analytical suitability
  • Spectral signatures distinguish vegetation, water, roofs and bare soil
  • Band combinations enhance features for visual interpretation and digitising
  • Supervised classification uses training samples and confusion matrices
  • NDVI calculations identify vegetation condition from red and near-infrared bands
  • Raster calculator applies conditional expressions, reclassification and weighted overlays

Participants can interpret imagery and report change-detection findings with stated limitations.

  • Image acquisition dates aligned with seasonal, incident and survey requirements
  • Atmospheric, cloud and shadow effects assessed before interpretation
  • Ground-truth observations designed to verify remotely sensed classes
  • Change detection compares classified imagery across defined observation periods
  • Classification accuracy reported using producer, user and overall accuracy
  • Interpretation limits recorded for resolution, timing, occlusion and sensor effects

Participants can design clear, accurate and accessible maps for defined users.

  • Visual hierarchy uses size, colour, weight and placement purposefully
  • Sequential, diverging and categorical colour schemes matched to data types
  • Classification methods compare natural breaks, quantiles, equal intervals and standard deviation
  • Labels configured with hierarchy, conflict detection and scale-dependent visibility
  • Map layouts include title, legend, scale, sources, date and projection
  • Accessibility checks assess colour contrast, symbol discrimination and readable typography

Participants can prepare and publish controlled web map products for target users.

  • Web map layers prepared with appropriate fields, scales and pop-ups
  • Tile, feature and image services selected for intended use
  • Layer symbology simplified for browser performance and audience understanding
  • Interactive filters, bookmarks and hyperlinks support focused map exploration
  • Sharing permissions control internal, partner and public access
  • Publishing checklist verifies attribution, metadata, rendering and service status

Participants can create transparent spatial analyses to compare decision options.

  • Suitability models combine weighted criteria, constraints and exclusion rules
  • Multi-criteria evaluation documents weights, assumptions and stakeholder priorities
  • Network analysis calculates routes, service areas and closest facilities
  • Spatial statistics identify clusters, outliers and distribution patterns
  • Scenario maps compare alternatives using consistent criteria and thresholds
  • Decision briefings distinguish observed evidence from analytical assumptions

Participants can apply governance controls to GIS data, services and published outputs.

  • ISO 19115 metadata profiles define discovery, lineage and quality fields
  • OGC service standards guide interoperable map and feature delivery
  • Data dictionaries specify definitions, units, valid values and custodians
  • Licensing terms reviewed for basemaps, imagery, open data and reuse
  • Privacy controls minimise personal location data and restrict disclosure
  • Retention schedules govern archival, deletion and record preservation

Participants can design repeatable GIS processing workflows and basic automation controls.

  • ModelBuilder and QGIS Processing models chain repeatable geoprocessing steps
  • Python scripts parameterise imports, validation checks and scheduled exports
  • Batch processing applies consistent projections, naming and folder structures
  • Reusable parameters separate business inputs from fixed analytical logic
  • Processing logs capture tool settings, messages, duration and outputs
  • Automation tests compare expected features, counts and attribute values

Participants can plan GIS work, manage delivery risks and define acceptance controls.

  • Project plans sequence collection, cleaning, analysis, review and publication tasks
  • Work breakdown structures assign roles, dependencies, estimates and milestones
  • Risk registers address access, safety, weather, connectivity and data loss
  • Acceptance criteria define positional, attribute, completeness and cartographic thresholds
  • Stakeholder review points approve scope, prototypes, findings and releases
  • Change control records requests, impact assessment, decisions and implementation

Participants can present GIS findings with appropriate evidence, limitations and documentation.

  • Map series and atlas outputs standardise recurring reporting products
  • Analytical findings structured for executives, technical reviewers and field teams
  • Uncertainty statements explain confidence, limitations and appropriate decision use
  • Data visualisations pair maps with charts, tables and concise annotations
  • Technical methods notes document sources, processing, parameters and validation
  • Peer review criteria assess correctness, clarity, traceability and usability

Participants can build, review and present a complete GIS data collection, analysis and mapping product.

  • Client brief converted into scope, questions, data specification and delivery plan
  • Field or supplied data ingested, documented, cleaned and quality-checked
  • Spatial analysis produces defensible findings against stated decision criteria
  • Cartographic product communicates results through labelled maps and supporting visuals
  • Metadata, methods note and QA evidence assembled for handover
  • Peer review resolves defects before stakeholder presentation and final release

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. GIS data collection specification template
  2. Geodatabase data model and dictionary
  3. Field collection and GNSS control plan
  4. Spatial data quality assurance checklist
  5. Spatial analysis methods note
  6. Completed GIS project portfolio package

Who should attend

  • GIS Analysts — need repeatable methods for producing trusted spatial datasets and maps
  • Survey and Field Officers — need reliable mobile collection workflows and GNSS controls
  • Asset Managers — need accurate location records for infrastructure, facilities and equipment
  • Urban and Regional Planners — need spatial evidence for land use and service planning
  • Environmental Specialists — need imagery interpretation and monitoring methods
  • Programme and Monitoring Officers — need defensible maps for operational reporting and decisions

Skills and tools covered

GIS data modellingField data collectionSpatial data qualityRaster image analysisCartographic communicationSpatial decision analysis

Tools and standards

QGIS, ArcGIS Pro, ISO 19115, OGC standards

How the course runs

Training methodology

Instruction uses short technical briefings followed by guided work on realistic GIS cases such as utility asset surveys, flood exposure mapping, site selection and environmental monitoring. Participants configure data structures, assess source data, build collection forms, run spatial analyses and prepare map products. Group reviews use defined quality criteria to identify errors in geometry, attributes, projections and map communication. Trainers adapt datasets and scenarios to the cohort’s sector, then support individual application planning for workplace projects.

Requirements and prerequisites

Participants should understand basic map concepts, including points, lines, polygons, layers and attribute tables. They should be comfortable working with spreadsheets, file folders and standard desktop software. Prior use of GIS software is helpful; participants should ideally have created or edited simple layers before attending. The course assumes an ability to interpret operational data and work with coordinates, but it does not require programming experience, advanced statistics, surveying qualifications, remote sensing expertise or prior use of a specific GIS platform.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

Participants should understand basic GIS layers, attribute tables and map concepts, and be comfortable with standard desktop software. Prior experience creating or editing simple GIS data is helpful, but programming, surveying and remote sensing qualifications are not required.

For classroom delivery, participants receive access to the required training environment and datasets. For live online delivery, participants need a computer capable of running the agreed GIS software, reliable internet access and a second screen if available.

The course is designed for GIS analysts, field officers, planners, asset managers, environmental specialists and programme staff. It is most useful for people who need to create, check, analyse or commission spatial data products.

Basic GIS courses usually focus on software orientation and simple map creation, while remote sensing courses may concentrate mainly on image interpretation. This course connects field collection, data modelling, quality control, vector and raster analysis, cartography, publishing and documented project delivery.

Participants can apply the methods to asset inventories, inspection programmes, site selection, service coverage, environmental monitoring, incident mapping and operational reporting. The templates and project package can be adapted to existing data standards and approval processes.

Each training day runs from 08:30 to 16:30 and provides about 6.5 contact hours. The first week establishes data collection, data modelling, quality and core analysis methods; the second week develops imagery, cartography, publishing, automation, governance and a final project presentation.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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