GIS, Spatial Databases & Geospatial Data Management Training

Course overview

GIS, Spatial Databases & Geospatial Data Management Training provides practical skills for collecting, organising, storing, managing, querying and analysing geospatial data within modern GIS and database environments. The course covers spatial database design, coordinate systems, vector and raster data, spatial queries, data relationships, geodatabase development, data quality, spatial indexing, data integration, GIS database administration and the use of spatial databases to support mapping and spatial analysis. Participants also explore practical applications using technologies such as PostGIS, PostgreSQL, QGIS, ArcGIS and GeoServer, enabling them to build structured geospatial data systems for urban planning, land administration, environmental management, infrastructure, agriculture, utilities, disaster management and other location-based applications.

Course objectives

• Design and develop spatial databases for efficiently storing, organising and managing vector, raster and attribute-based geospatial information.
• Create, manage and query geospatial data using spatial database technologies such as PostgreSQL/PostGIS and integrate them with GIS platforms.
• Apply spatial queries, relationships, indexing and geoprocessing techniques to retrieve, analyse and manipulate location-based information efficiently.
• Integrate GIS, spatial databases and web-mapping technologies to support applications in urban planning, land administration, environmental management, infrastructure, agriculture and other location-based sectors.
• Implement effective geospatial data-management practices covering data quality, coordinate reference systems, metadata, data validation, security, interoperability and maintenance of reliable GIS databases.

Who should attend

Course content

• Module 1: Foundations of GIS and Spatial Database Management GIS concepts and components, spatial data and geographic information, GIS versus conventional databases, spatial database concepts, spatial objects and attributes, vector and raster data, spati
• Module 2: Spatial Data Models and Geographic Information Structures Point, line and polygon data, multipoint and multipart geometries, raster datasets, geometry and geography concepts, spatial attributes, feature classes, layers and tables, relationships
• Module 3: Coordinate Reference Systems and Spatial Data Accuracy Geographic coordinate systems, projected coordinate systems, datums, map projections, coordinate transformations, EPSG codes, spatial reference identifiers, measurement units, positional ac
• Module 4: Spatial Database Design and Data Modelling Requirements analysis, conceptual database design, logical database design, entity-relationship modelling, spatial entities, attributes and relationships, primary and foreign keys, normalisation, spati
• Module 5: PostgreSQL and PostGIS for Spatial Data Management PostgreSQL database fundamentals, PostGIS architecture, enabling spatial extensions, creating spatial databases, geometry and geography columns, spatial tables, geometry types, importing GIS da
• Module 6: Spatial Data Import, Conversion and Integration Importing Shapefiles, GeoJSON, GeoPackage, CSV and other datasets, loading raster information, data conversion, schema matching, field mapping, geometry validation, handling different coordinate s
• Module 7: Spatial SQL and Geospatial Querying SQL fundamentals for GIS users, SELECT and filtering operations, joins, aggregation, subqueries, spatial functions, geometry relationships, distance queries, intersection queries, containment queries, proximi
• Module 8: Spatial Analysis Using Database Functions Buffering, intersection, clipping, union and difference, distance calculations, centroid generation, geometry transformations, area and length calculations, proximity analysis, overlay operations, spati
• Module 9: Spatial Indexing and Database Performance Optimisation Purpose of spatial indexes, GiST indexes, R-tree concepts, SP-GiST, spatial query optimisation, index-aware functions, execution plans, query performance, database statistics, large geospat
• Module 10: Geospatial Data Quality, Validation and Governance Spatial data quality principles, positional accuracy, attribute accuracy, completeness, consistency, duplicate detection, invalid geometries, topology errors, missing values, geometry repair,
• Module 11: GeoPackage, Interoperability and Open Geospatial Standards GeoPackage structure and applications, SQLite-based geospatial storage, vector and raster tiles, portable spatial databases, data exchange, OGC standards, WMS, WFS, OGC APIs, GeoJSON,
• Module 12: Connecting Spatial Databases with GIS Platforms Connecting PostgreSQL/PostGIS to QGIS, connecting spatial databases to ArcGIS environments, database browsing, loading spatial layers, editing database features, executing spatial SQL from GIS, s
• Module 13: Enterprise Geospatial Data Management and Web GIS Centralised spatial databases, multi-user editing, user roles and permissions, enterprise geodatabases, GeoServer integration, publishing spatial database layers, WMS and WFS services, web mapp
• Module 14: Advanced Spatial Database Applications and Geospatial Analytics Location-based queries, proximity services, spatial decision support, multi-criteria spatial analysis, temporal spatial data, 3D geometries, large-scale geospatial datasets, real-
• Module 15: Geospatial Data Management Projects and Advanced Applications End-to-end spatial database project development, database requirements assessment, spatial schema design, data loading and validation, spatial SQL development, spatial indexing, GIS

General notes

• Practical Application Areas Urban planning and land administration, cadastral and property management, environmental monitoring, agriculture and natural-resource management, infrastructure and utility management, transport and logistics, public health, disaster risk management, humanitarian operations, crime and security mapping, environmental assessment, smart-city applications, asset management and location-based decision support
• Suggested Practical Tools PostgreSQL and PostGIS, QGIS, ArcGIS, GeoPackage, GeoServer, SQL, Python for geospatial automation, GDAL/OGR and web-based geospatial services. The specific software combination can be adapted to the participants' professional environment.

Frequently asked questions

Schedule & fees