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Practical Session: Geoprocessing, Table Operations, and Zonal Statistics

This hands-on session walks you through coordinate transformations, vector geoprocessing (buffering, clipping), calculating catchment stats using zonal statistics, and using the Field Calculator to compute geometric values.

1. Setting Up the Workspace and Data Inputs

Before beginning the analysis, establish your data links and workspace inside QGIS:

  1. Open QGIS and create a new project. Save it as Day3_Vector_Analysis.qgz in your project folder.

  2. In the Browser Panel, add a directory shortcut to your training folder.

  3. Load the following input datasets:

  4. river_network.gpkg (Linear stream network of study basin).

  5. sub_catchments.gpkg (Polygon boundaries of catchment sub-zones).

  6. elevation_dem.tif (Continuous elevation raster grid, e.g., Copernicus DEM).

2. Reprojecting Layers to a Projected Coordinate System

Before running proximity buffers or calculating polygon areas, datasets must use projected metric coordinates (meters) rather than spherical degrees (degrees).

  1. Go to Processing > Toolbox and search for the Reproject Layer tool.

  2. Run the tool on river_network.gpkg:

  3. Input Layer: river_network.gpkg.

  4. Target CRS: Select WGS 84 / UTM Zone 45N (EPSG:32645) (the appropriate projected system for Nepal).

  5. Save the reprojected layer to data/processed/vector/rivers_projected.gpkg.

  6. Repeat the reprojection steps for the sub_catchments.gpkg boundaries and save the output as data/processed/vector/catchments_projected.gpkg.

  7. Remove the original unprojected layers from the Layers Panel to prevent formatting mistakes.

3. Creating a Dissolved Riparian Buffer Corridor

Delineate a \(500\text{ meter}\) environmental protection buffer corridor surrounding all major rivers:

  1. Navigate to Vector > Geoprocessing Tools > Buffer.

  2. Input Layer: rivers_projected.gpkg.

  3. Distance: Enter 500 (make sure the unit dropdown is set to meters).

  4. Segments: Enter 5 (determines roundness of buffer corners).

  5. Check the box for Dissolve result. This merges overlapping buffers from adjacent river sections into a single continuous polygon.

  6. Buffered: Click ... > Save to GeoPackage. Naming:

  7. File path: data/processed/vector/catchment_analysis.gpkg

  8. Table name: riparian_buffer_500m

  9. Click Run. Toggle the layer styling to a semi-transparent blue fill to verify the buffer corridor surrounds the rivers correctly.

4. Clipping Geoprocessing Outputs

Clip the river buffer corridors to the specific boundary of a target sub-catchment to limit our study scope:

  1. Navigate to Vector > Geoprocessing Tools > Clip.

  2. Input Layer: riparian_buffer_500m (the layer to be cut).

  3. Overlay Layer: catchments_projected.gpkg (the polygon boundary acting as the cookie-cutter).

  4. Clipped: Click ... > Save to GeoPackage inside catchment_analysis.gpkg. Naming the table: study_corridor_clipped.

  5. Click Run. A new layer will appear showing only the buffers that fall inside the catchment boundary.

5. Zonal Statistics Laboratory

Extract topographic elevations for each sub-catchment polygon from the digital elevation grid:

  1. Search for Zonal Statistics in the Processing Toolbox.

  2. Set the tool parameters:

  3. Raster Layer: elevation_dem.tif.

  4. Vector Layer containing zones: catchments_projected.gpkg.

  5. Output Column Prefix: Enter dem_ (this flags the generated columns).

  6. Click Statistics to calculate (...) and check Mean, Min, and Max.

  7. Zonal Statistics (Output): Set to save the updated table to a new table catchments_elev_stats inside catchment_analysis.gpkg.

  8. Click Run.

  9. Right-click the newly created catchments_elev_stats layer in the Layers panel and select Open Attribute Table. Scroll to the far right to verify that three new columns (dem_mean, dem_min, dem_max) contain the extracted elevations for each catchment.

6. Dynamic Area Calculations via the Field Calculator

Calculate the total area in square kilometers (\(km^2\)) for each catchment polygon using database equations:

  1. Open the attribute table of the catchments_elev_stats layer.

  2. Click the Toggle Editing Mode icon (the pencil icon, or press Ctrl+E).

  3. Click the Open Field Calculator icon (the abacus icon, or press Ctrl+I).

  4. Configure the Field Calculator parameters:

  5. Check Create a new field.

  6. Output field name: Enter area_sqkm.

  7. Output field type: Select Decimal number (real).

  8. Precision: Set to 2 (places after the decimal).

  9. In the expression editor panel, enter the geometry calculation formula: $area / 1000000

  10. Click OK. QGIS will compute and add the area values to every row.

  11. Click the Save Edits icon and press Ctrl+E to toggle editing mode off.

7. Practical Session Exercises (Basic to Advanced)

The following 10 exercises test your geoprocessing, attribute querying, data conversion, and neighborhood analysis skills. They utilize various scales (110m, 50m, 10m) of cultural, physical, vector, and raster datasets available in your project directory.

Basic Level

Exercise 1: Multi-Scale Layer Properties and Feature Counts

Analyze the effect of cartographic scale and generalization on vector geometries.

  1. Load ne_110m_admin_0_countries.shp (coarse scale) and ne_50m_admin_0_countries.shp (medium scale) from 110m_cultural and 50m_cultural folders.

  2. Open the Layer Properties > Information for both layers and identify the difference in coordinates precision and file sizes.

  3. Open their Attribute Tables. Report the exact feature count (number of countries) contained in the 110m layer vs. the 50m layer.

Exercise 2: Projected Metric Lake Area Calculation

Calculate lake areas in projected metric units rather than spherical degrees.

  1. Load the physical polygon layer ne_50m_lakes.shp from the 50m_physical folder.

  2. Use the Reproject Layer tool to project the lakes into a metric CRS: WGS 84 / UTM Zone 45N (EPSG:32645). Save the output as lakes_utm.gpkg.

  3. Open the Field Calculator on lakes_utm.gpkg and create a new decimal field named lake_area_sqkm. Use the formula: $area / 1000000

  4. Sort the table by lake_area_sqkm in descending order to identify the largest lake feature in the region.

Exercise 3: Landlocked African Country Attribute Selection

Perform attribute-based queries to filter specific spatial subsets.

  1. Load ne_110m_admin_0_countries.shp.

  2. Open Select by Expression (Ctrl+F3) and run the following query to select landlocked African countries with population over 10 million: 

    "continent" = 'Africa' AND "pop_est" > 10000000 AND "featurecla" = 'Admin-0 country'
    (Hint: You can check the attribute table structure to identify which columns contain landlocked flags or filter boundaries).

  3. Save the selected features to a new layer named large_landlocked_africa.shp.

Exercise 4: Continental Boundary Dissolve

Aggregate national political boundaries into global continental shapes.

  1. Load ne_50m_admin_0_countries.shp into your canvas.

  2. Go to Vector > Geoprocessing Tools > Dissolve.

  3. Set the parameters:

  4. Input Layer: ne_50m_admin_0_countries.shp.
  5. Dissolve field(s): Check the box for continent.

  6. Dissolved: Save to database as continents_dissolved.

  7. Click Run and verify that internal national border lines are merged, leaving only continental outlines.

Intermediate Level

Exercise 5: Riparian Buffer Corridors of Major Rivers

Create metric proximity buffers around primary stream centerlines.

  1. Load ne_50m_rivers_lake_centerlines_scale_rank.shp from 50m_physical.

  2. Select the major continental rivers where scale rank is highest: "scalerank" <= 2.

  3. Use Reproject Layer to reproject the selected river segments to WGS 84 / UTM Zone 45N (EPSG:32645) and save as major_rivers_projected.gpkg.

  4. Run the Buffer tool on major_rivers_projected.gpkg with a distance of 20 Kilometers, checking the box for Dissolve result. Save the output as river_buffers_20km.

Exercise 6: Map Algebra Masking on Shaded Relief

Create a binary raster grid classifying shaded relief brightness values.

  1. Load the shaded relief raster NE1_50M_SR_W.tif from the 50m_raster folder.

  2. Open Raster > Raster Calculator.

  3. Write an expression to isolate dark valley/shadow pixels (brightness value less than 100): 

    "NE1_50M_SR_W@1" < 100

  4. Save the output as dark_relief_mask.tif. Verify that the output pixels contain only \(1\text{s}\) (shadows) and \(0\text{s}\) (bright surfaces).

Exercise 7: Spatial Join of Cities and Countries

Transfer political attributes to point-based populated places by spatial location.

  1. Load ne_50m_populated_places.shp (points) and ne_50m_admin_0_countries.shp (polygons).

  2. Go to Vector > Data Management Tools > Join Attributes by Location.

  3. Set the parameters:

  4. Input Layer: ne_50m_populated_places (features to be joined to).
  5. Join Layer: ne_50m_admin_0_countries.
  6. Geometric predicate: Select within.
  7. Fields to add: Click ... and check name and iso_a3.
  8. Join type: Take attributes of the first matching feature.

  9. Joined layer: Save as cities_joined_countries.

  10. Open the attribute table of cities_joined_countries and verify that the country details are appended to each city point.

Advanced Level

Exercise 8: Zonal Statistics of Shaded Relief across South Asia

Calculate topographical texture summary statistics for South Asian countries.

  1. Load the shaded relief raster NE1_50M_SR_W.tif and the countries vector ne_50m_admin_0_countries.shp.

  2. Filter the countries layer to select South Asian countries: Open Select by Expression on the countries layer and run: 

    "subregion" = 'Southern Asia'

  3. Open Zonal Statistics in the Processing Toolbox.

  4. Set the parameters:

  5. Raster Layer: NE1_50M_SR_W.tif.
  6. Vector Layer containing zones: ne_50m_admin_0_countries (check Selected features only).
  7. Output Column Prefix: Enter sr_.
  8. Statistics to calculate: Select Mean, Min, and Max.

  9. Zonal Statistics: Save as south_asia_relief_stats.

  10. Run the tool. Inspect the output table and identify which South Asian country contains the lowest minimum shaded brightness (indicating the deepest valleys/shadows).

Exercise 9: Vectorizing DEM Peaks and Clipping to Nepal

Extract high-altitude mountain peaks as vector polygons and clip them to national bounds.

  1. Load the continuous DEM grid output_hh.tif from the DEM folder and the high-resolution countries layer ne_10m_admin_0_countries.shp from 10m_cultural.

  2. Open Raster Calculator and generate a binary mask of peaks higher than \(5500\text{ meters}\): 

    "output_hh@1" > 5500
    Save the output as peaks_mask_5500m.tif.

  3. Open Raster > Conversion > Polygonize (Raster to Vector). Run it on peaks_mask_5500m.tif with a field name is_peak to create a polygon layer named peaks_vector.

  4. Filter peaks_vector to keep only peak polygons: Select features where "is_peak" = 1 and save them to a new layer high_altitude_peaks_only.

  5. Filter ne_10m_admin_0_countries.shp for Nepal ("NAME" = 'Nepal').

  6. Run Vector > Geoprocessing Tools > Clip to clip the high_altitude_peaks_only polygons using the Nepal boundary polygon. Save the final output as nepal_peaks_clipped.

Exercise 10: Multi-Criteria Spatial Query and Proximity Matrix

Identify major cities located in close proximity to main continental river channels.

  1. Load ne_10m_populated_places.shp (points) and ne_10m_rivers_lake_centerlines.shp (lines).

  2. Select major cities with population greater than 1 million: Open Select by Expression on the populated places layer and run: 

    "pop_max" > 1000000
    Save the selected features to a new layer named major_cities.

  3. Select major rivers where scale rank is high: Open Select by Expression on the rivers layer and run: 

    "scalerank" <= 3
    Save the selected segments to a new layer named primary_rivers.

  4. Search for the Distance to nearest hub (points) tool in the Processing Toolbox.

  5. Set the parameters:

  6. Source points layer: major_cities.
  7. Destination hubs layer: primary_rivers.
  8. Hub layer name attribute: Select name (the river name field).
  9. Measurement unit: Select Kilometers.

  10. Hub distance: Save the output points as cities_to_rivers_proximity.

  11. Run the tool. Open the attribute table of cities_to_rivers_proximity. Use Select by Expression to identify which major cities lie within \(15\text{ km}\) of these major rivers: 

    "HubDist" <= 15

13. Guided Mini-Assignment: Building a Hydrological GIS Database

In this assignment, you will apply the skills learned during Day 3 to clean vector datasets, execute spatial joins, calculate catchment statistics, compute geometric attributes, and compile a formatted layout map. This assignment is designed to require approximately 1 hour to complete.

Objective

Build a structured, centralized hydrological database inside a single GeoPackage file. You will calculate sub-basin average elevations, stream network lengths, and riparian buffer corridors, and export a cartographically sound print layout map illustrating your analytical results.

Provided Datasets

The following raw layers are located in your project directory: * /data/vector/raw_districts.shp (Administrative boundary polygons, EPSG:4326).

  • /data/vector/river_branches.gpkg (Polyline stream centerlines, EPSG:4326).

  • /data/raster/terrain_elevation.tif (Digital elevation model raster grid, EPSG:4326).

Step-by-Step Requirements

Step 1: Database Initialization and Reprojection

  1. In the QGIS Browser panel, right-click a local folder and create a new OGC GeoPackage database file named Basin_Hydrology_Database.gpkg.

  2. Import the raw raw_districts.shp and river_branches.gpkg layers.

  3. Reproject both layers into the metric UTM Zone 45N projection (EPSG:32645) to ensure all calculations use meter units. Store the reprojected tables inside Basin_Hydrology_Database.gpkg as:

  4. district_boundaries
  5. river_centerlines

Step 2: Proximity Buffer Analysis

Delineate a riparian conservation corridor around the river network:

  1. Run the Buffer tool on river_centerlines.

  2. Set the buffer distance to \(250\text{ meters}\).

  3. Check the box to Dissolve result to merge overlapping stream buffers.

  4. Save the output table directly inside your GeoPackage database as riparian_buffer_250m.

Step 3: Zonal Statistics and Attribute Calculations

Extract elevation statistics and calculate geographic metrics for the administrative districts:

  1. Run the Zonal Statistics tool:
  2. Raster Layer: terrain_elevation.tif.
  3. Vector Layer (Zones): district_boundaries.
  4. Output Prefix: elev_.

  5. Statistics: Calculate Mean and Max.

  6. Save the output table in your GeoPackage as districts_elevation_summary.

  7. Open the attribute table of districts_elevation_summary. Turn on editing mode (Ctrl+E) and open the Field Calculator (Ctrl+I):

  8. Create a new field named area_sqkm (Decimal number, Precision: 2). Formula: $area / 1000000
  9. Save changes and toggle editing mode off.

Step 4: Map Layout and Cartography

Create a publication-quality map of your study area:

  1. Open a new Print Layout and set the page size to A4 Landscape.

  2. Add a map frame rendering the following layers:

  3. Top Layer: riparian_buffer_250m styled in semi-transparent light blue (Hex #4a90e2) with a dashed border.
  4. Middle Layer: river_centerlines styled as thin blue lines.

  5. Bottom Layer: districts_elevation_summary styled using Graduated Symbology based on the elev_mean field. Apply a Viridis or YlOrRd color ramp, classified into \(5\) bins using Jenks Natural Breaks.

  6. Add the following cartographic elements to the layout page:

  7. Title Block: "Administrative District Elevation and Riparian Buffer Map".
  8. Scale Bar: Dynamic metric scale bar (labeled in km).
  9. North Arrow: Placed in an open quadrant.
  10. Legend: Clear labels for each active layer. Clean up raw column name entries (e.g. rename elev_mean range bins to "Average Elevation (meters)").
  11. Map Grid (Graticule): Add coordinate lines displayed in UTM meter values along the map borders.

Submission Instructions

Export your layout map as a PDF. Compile a ZIP archive named Day3_Assignment_[YourName].zip containing:

  1. The exported PDF map (District_Elevation_Buffer_Map.pdf).

  2. The completed GeoPackage database container (Basin_Hydrology_Database.gpkg) containing all four tables.

  3. The QGIS project configuration file (Day3_Assignment.qgz) saved with relative data paths.