Calculating Raster Class Areas ¶

QGIS raster functionality continues to advance. The author discovered an interesting question on GIS Stack Exchange about calculating the area of each class in a raster dataset.

Initial Suggested Approach (Three-Step Method) ¶

• Recode the raster to simplify classes
• Vectorize the raster layer
• Calculate statistics from the vector layer using SQL or QGIS algorithms

Limitations of the Traditional Approach ¶

• Requires preprocessing using raster calculator or reclassify algorithms
• Vectorization is CPU-intensive; large rasters with limited resources cause prolonged processing times
• Generated statistics cannot be incorporated into the raster legend

Proposed Solution ¶

A PyQGIS-based approach utilizing Python GDAL and NumPy that generates summary statistics as part of the classification legend.

Procedure ¶

1. Download the script raster_classifier.py from the provided GitHub Gist link
2. Open the script in a text editor and modify the raster path to specify your single-band raster
3. Navigate to QGIS and open the Python console
4. Load and run the script; the classified raster loads into QGIS

Script Summary ¶

The script emulates QGIS GUI symbolization for single-band rasters:

• Input Requirements: Ideally projected rasters; EPSG:4326 converts to EPSG:3857; local or UTM projections recommended for accuracy
• get_raster_area function: Calculates total raster area by multiplying individual cell area by cell count
• get_area function: Uses NumPy to calculate area of each color range by identifying pixels within specified ranges
• mini_style function: Creates color ramp shader defining new color ranges for symbolization using interpolation for continuous data
• style_raster function: Defines color ranges, calculates percentage coverage per class relative to total area, creates six classes using min/max raster statistics

Final Output ¶

Classified raster displays legend with area calculation per class and percentage coverage statistics.