Analysis and Geoprocessing Tools in QGIS

Module 1: Introduction to Spatial Analysis and Geoprocessing

• Purposes and applications of spatial analysis

• Differences between data management, geoprocessing, and analysis

• Translating spatial questions into individual processing steps

• Using vector, raster, and tabular data as inputs

• Distinguishing inputs, parameters, intermediate results, and outputs

• Requirements relating to data quality and spatial accuracy

• Capabilities and limitations of automated analytical results

Module 2: The QGIS Processing Toolbox

• Structure and operation of the Processing Toolbox

• Searching for tools by name, provider, or function

• Distinguishing native QGIS tools from other Processing providers

• Defining input parameters and output options

• Using temporary and permanent results

• Examining processing history and log messages

• Organising frequently used tools as favourites

Module 3: Preparing Data for Analysis

• Checking geometries, attributes, and coordinate systems

• Selecting suitable input layers

• Identifying and repairing invalid or damaged geometries

• Reviewing attribute fields and data types

• Defining study areas and relevant data subsets

• Converting data into suitable formats

• Storing and naming analytical results systematically

Module 4: Attribute-Based Queries

• Selecting features by attribute values

• Creating simple and combined expressions

• Querying text, numerical, and date fields

• Using operators and logical conditions

• Handling missing or empty values

• Processing or exporting selected features

• Saving recurring queries as expressions

Module 5: Spatial Queries

• Understanding spatial relationships between features

• Selecting features that intersect, touch, or overlap

• Identifying features inside or outside a defined area

• Selecting features within a specified distance

• Combining spatial and attribute-based conditions

• Comparing selection methods and their effects

• Reviewing and documenting query results

Module 6: Spatial Joins

• Differences between attribute and spatial joins

• Transferring attributes according to spatial relationships

• Assigning point information to polygons

• Joining information through overlap or proximity

• Summarising multiple matching features

• Applying summary functions during spatial joins

• Identifying and handling unmatched features

• Preparing results for further analysis

Module 7: Buffer and Distance Analysis

• Creating buffers around points, lines, and polygons

• Selecting appropriate buffer distances and units

• Creating single and multiple buffer rings

• Dissolving overlapping buffers or retaining separate areas

• Examining one-sided and line-based buffers

• Mapping zones of influence and accessibility

• Overlaying buffers with other layers

• Assessing the meaning and limitations of distance analysis

Module 8: Clipping and Spatial Overlay

• Clipping layers to a study area

• Comparing Clip, Intersection, and Difference tools

• Combining geometries and attributes from multiple layers

• Identifying shared and non-shared areas

• Applying Union and Symmetrical Difference operations

• Managing geometry collections and different feature types

• Checking overlay results for completeness

• Selecting appropriate tools for different questions

Module 9: Merging, Dissolving, and Combining Data

• Dissolving neighbouring features by shared attributes

• Removing boundaries between related polygons

• Calculating statistics during a dissolve operation

• Merging multiple layers with similar structures

• Understanding the differences between Merge, Append, and Union

• Combining individual features or polygon parts

• Aligning field structures from different input datasets

• Reviewing and cleaning the results

Module 10: Splitting Layers and Datasets

• Dividing layers into multiple outputs by attribute value

• Separating data by region, category, or responsibility

• Exporting individual features as separate files

• Generating dynamic output names

• Creating spatial subsets for different work areas

• Organising dataset sizes and file structures

• Checking split outputs automatically