13 Analysis Tools
The three research questions in the last chapter introduced you to some of the most commonly used vector and raster analysis tools available in QGIS. Below, you will find a more detailed list of tools.
13.1 Vector Analysis Tools
13.1.1 Buffer
A buffer creates a zone around a selected feature (point, line, or polygon) at a specified distance.
Example: You are examining flood risk around streams (line vectors). Your first step may be to determine a reasonable area outside of the stream that you would want to examine for risk. Therefore, you might buffer the stream lines 150ft.
13.1.2 Variable Buffer
A variable buffer applies different distances to features based on a specific attribute in the dataset. Instead of a single distance for all features, each feature’s buffer size is determined by an existing data field.
Example: You are looking at noise pollution from roadways. High volume roads (such as highways) may have impacts at a further distance than low volume roads (like residential roads). You may choose to buffer high volume roads .5 miles and low volume roads .25 miles.
13.1.3 Clip
The clip tool extracts features from one dataset that fall within the boundary of another. The output contains only the features within the defined boundary while maintaining their original attributes.
Example: You have a dataset representing schools in North Carolina, but are only interested in schools in Orange County, so you clip the school dataset by a polygon representing Orange County boundaries
13.1.4 Merge
The merge tool combines multiple layers of the same feature type (points, lines, or polygons) into a single dataset without modifying geometries. Attributes from all input layers are preserved in the output dataset. If a field exists in one layer but not in another, QGIS fills the missing values with NULLs.
Example: You have a parcel dataset from Orange County and one from Alamance County and would like to analyze the data together.
13.1.5 Dissolve
Dissolve merges adjacent polygons that share a common attribute into a single, larger feature.
Example: You have a land cover dataset with a more detailed primary land cover and a simpler secondary land cover. You want to create polygons just based on the secondary land cover
13.1.6 Intersect
This tool extracts the portions of features from the input layer that overlap features in the overlay layer. Features in the intersection layer are assigned the attributes of the overlapping features from both the input and overlay layers.
Example: You have a dataset of flood zones and another of residential parcels. You use the intersect tool to identify and extract only the parts of residential parcels that fall within flood zones, combining the attributes from both datasets in the output.
13.1.7 Union
Union combines two polygon layers while preserving all features and attributes from both. Unlike intersection, it keeps all areas from both input layers. This tool checks overlaps between features within the input layer and creates separate features for overlapping and non-overlapping parts. The area of overlap will create as many identical overlapping features as there are features that participate in that overlap.
Example: You are analyzing both zoning areas and historic district boundaries. You use the union tool to combine the two polygon layers so that each resulting polygon shows both its zoning category and whether or not it is in a historic district.
13.1.8 Difference
The difference tool subtracts one layer from another, keeping only the portions of the input layer that do not overlap with the second layer. The output layer contains only the unique portions of the input dataset.
Example: You want to identify areas within a park boundary that are not occupied by water features. You use the difference tool to subtract the water feature polygons from the park polygon.
13.1.9 Symmetrical Difference
Similar to the difference tool, this process removes areas of overlap but keeps the unique portions of both input layers. The resulting dataset excludes any areas that intersect, leaving only the areas that are exclusive to each input.
Example: You want to identify areas where two proposed zoning plans disagree. You use the symmetrical difference tool to remove the overlapping areas and keep only the zones that are unique to each plan.
13.1.10 Spatial Join
A spatial join transfers attributes from one dataset to another based on spatial relationships. Unlike a traditional table join, which relies on matching attribute values, a spatial join links records based on location.
Example: You have a layer of apartment buildings and a layer of census tracts with income data. You use spatial join to assign each apartment building the average income of the census tract it falls within.
13.1.11 Points-in-Polygon (Join Attributes by Location - Summary)
This tool counts or summarizes point data within each polygon feature. It is often used for aggregating information. The output layer retains polygon features with new statistical values.
Example: You want to count the number of businesses (points) within each zip code.
13.1.12 Table Join
A table join connects attribute data from different sources using a common field, such as an ID number. This process does not alter geometries but enriches the dataset with additional information.
Example: You have a zip code boundary dataset and health information (tabular) at the zip code level.
13.1.13 Voronoi Diagram
This tool creates polygons around a set of points so that each polygon contains all locations closest to its corresponding point. The resulting polygons divide space based on distance to the nearest input point.
Example: You are analyzing access to hospitals across a region. You create a Voronoi diagram around hospital locations to define the area closest to each hospital, helping visualize their service areas.
13.2 Raster Tools
13.2.1 Raster Math
This process performs mathematical operations on raster data to modify or analyze values.
Example: You subtract a temperature raster from a historical average raster to map recent anomalies in surface temperature.
13.2.2 Extract by Mask
This tool clips a raster dataset using a vector boundary, keeping only the raster cells within the specified area. The output retains the original raster values but is spatially confined to the selected area.
Example: You clip a land cover raster to the boundary of a national park to analyze vegetation types only within the protected area.
13.2.3 Sample Raster Values
This tool extracts pixel values from a raster dataset at specific locations, typically defined by point features.
Example: You extract elevation values at wildlife observation points to study habitat preferences by elevation.
13.2.4 Reclassify Raster
This process assigns new values to raster cells based on classification rules
Example: You reclassify a land cover raster so that all forest types are grouped under a single “forest” category for simplified analysis.
13.2.5 Hillshade
Hillshade generates a shaded relief map based on elevation, simulating how light and shadow affect terrain.
Example: You generate a hillshade from a DEM to visually emphasize terrain for a printed topographic map.
13.2.6 Slope and Aspect
These tools derive terrain characteristics from elevation data. The slope tool calculates the steepness of the terrain, while the aspect tool determines the direction a surface faces.
Example: You calculate slope and aspect to determine suitable areas for solar panel installation, avoiding steep and north-facing slopes.
13.2.7 Contour Lines
This tool converts elevation raster data into contour lines representing constant elevation values. The output is a vector dataset of elevation curves.
Example: You create contour lines from elevation data to show terrain features on a hiking trail map.
13.2.8 Georeferencing
Georeferencing aligns raster images to real-world coordinates by assigning control points to known locations.
Example: You georeference a scanned historical map of Carrboro so that you can use it as a basemap for comparison with current data.
13.3 Selection, Description, and Summary Tools
13.3.1 Select by Attribute
This tool filters data based on attribute values using SQL-like expressions.
Example: You select all parcels where the zoning code is “R-10” to identify areas designated for medium-density residential development.
13.3.2 Select by Location
This tool selects features based on their spatial relationship to another dataset
Example: You select all schools that fall within 500 meters of a major road to analyze noise exposure risks.
13.3.3 Zonal Statistics
This tool calculates statistical values (sum, mean, max, etc.) for raster data within defined polygon boundaries. The output adds fields to a new polygon output with statistical values from the raster
Example: You calculate the average elevation within each watershed to assess how terrain might influence streamflow patterns.
13.3.4 Field Calculator
This tool allows users to create or modify attribute fields using formulas and expressions.
Example: You create a new field that multiplies area by a tax rate to estimate potential revenue from each land parcel.
13.3.5 Aggregate Statistics
This tool computes summary statistics for grouped attributes within a dataset.
Example: You calculate the mean household income for each county by grouping census block data by county boundaries.
13.4 Other Tools
13.4.1 Batch Processing
This tool automates repetitive spatial operations by running them on multiple datasets simultaneously.
Example: You batch convert dozens of shapefiles to GeoPackages to standardize your project’s data format.
13.4.2 Model Designer
The model designer allows users to create workflows that chain multiple QGIS processes into a single automated operation. Once designed, models can be reused for similar analyses.
Example: You build a model that automatically clips, reprojects, and joins land use data for each new municipality added to your project.