PostgreSQL geo-spatial data management with PostGIS
LEVEL: Expert
In this comprehensive course, participants will learn the basics and advanced techniques of spatial data processing with PostGIS, a powerful extension for PostgreSQL that makes it possible to efficiently store, manage and analyse geographic information. The course combines theoretical knowledge with practical exercises to give participants a deep understanding of spatial data processing.
Use complex spatial functions to analyse and process data.
Gain practical experience in handling spatial data sets.
Target audience
Database Administrator
GIS Analysts
Developers
Prerequisites
Basic knowledge of geodata:
Participants should have a basic understanding of geographic information systems (GIS) and spatial data. This includes knowledge of different types of geospatial data, coordinate systems and spatial relationships.
Familiarity with PostgreSQL:
A basic knowledge of PostgreSQL is required, especially with regard to database structures, queries and basic SQL skills. Participants should be familiar with the PostgreSQL database environment.
Recommendation: Participation in the course ‘PostgreSQL Administration & Performance Tuning’:
It is recommended to complete the PostgreSQL Administration and Performance Tuning course beforehand. This ensures that participants have the necessary administrative skills and knowledge.
What you will learn
Proficiency in the installation and maintenance of PostGIS: Students will be able to install, configure and regularly maintain PostGIS in PostgreSQL environments to ensure system performance and stability.
Competence in using spatial data types and indices: Ability to identify and efficiently use various spatial data types, such as Geometry and Geography, and implement GIST, SP-GIST, and BRIN indexes, to optimise query speed.
Demonstrate advanced skills in the application of spatial functions: Master the use of a variety of spatial functions for data analysis, including topological relationships, measurement functions and special functions for geospatial data processing.
Practical experience in processing and validating spatial data: Ability to import, validate and clean spatial data to ensure that data integrity and quality is maintained.
Competence to analyse and visualise spatial data: Learn to analyse spatial data and effectively present the results, using appropriate visualisation techniques to gain insights from the data and communicate these clearly.
Architecture and functionality of PostGIS: Gain knowledge of the internal architecture of PostGIS, including the integration of spatial data types and indexes into the PostgreSQL database, and their interaction with other GIS tools and applications.
Application of spatial functions for data analysis: Become familiar with the various spatial functions available in PostGIS and understand how these functions can be used to solve complex geographic problems.
Course content
Module 1: Introduction to PostGIS and spatial data processing
Introduction to PostGIS and its importance in spatial data processing.
Installation and configuration of PostGIS in a PostgreSQL environment.
Overview of tools for import, export and ETL (Extract, Transform, Load).
Module 2: Spatial data types, indices and projections
Introduction to the various spatial data types:
Geometry (2D and 3D)
Geography (geodetic data)
Raster
Introduction to projections and transformations:
Using functions such as ST_Transform, to project spatial data into different coordinate systems.
Introduction to the use of SRIDs (Spatial Reference IDs) for the definition of projections.
Understanding and implementation of spatial indices:
GIST (Generalised Search Tree)
SP-GIST and BRIN (Block Range INdex)
Module 3: Raster data processing
Introduction to the raster data type and its properties
Dealing with raster files:
Importing raster data (e.g. GeoTIFF).
Management of raster data in PostGIS.
Processing of raster data.
Module 4: Spatial functions
Introduction to the core functions of PostGIS:
Output, construction, access and setter functions.
Measurement, composition, decomposition and simplification functions.
Application of topological functions:
Bounding boxes, equality checks and spatial relationships.
Spatial joins for linking data sets.
Special functions for processing and analysis:
Spatial aggregation, clipping, splitting, tessellation, segmentation, as well as translation, scaling and rotation.
Module 5: Practical application and exercises
Introduction to the data set and practical exercises:
Import and export of spatial and raster data.
Validation and correction of spatial and raster data.
Analysis of spatial data to gain insights.
Optional, not included by default
Module 6: Custom data sets
Bring your own data for
Import
Analysis
Visualisation
Course materials and environment
We will provide access to a dedicated tab environment and virtual machines running a Linux distribution.
Upon completion of the course, participants will receive a PDF of the slide deck that was used during the training sessions.
All scripts and configuration files present on the virtual machines during training will be available for download and use.
Upon completion of the course, participants will receive a complimentry copy of the most recent edition of Hans-Jürgens Schönig’s book Mastering PostgreSQL.
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