Day 78: Contour Generation & Smoothness Control – Masterpiece Edition | River Warrior

🗺️ DAY 78: CONTOUR GENERATION & SMOOTHNESS CONTROL

⏱️ Estimated Reading Time: 15 Minutes | 🎓 Level: Professional Hydrographer / Cartographer

From Grid to Line – Creating Clean, Navigation‑Ready Contours

Instructor: Engr. Rokib Hossain | River Warrior Academy

🏠 Course Homepage

📖 Table of Contents (Serialised)

Why Contours Are the Language of the Seabed
Contouring Algorithms: Linear, Spline, and Quadratic
Choosing the Right Contour Interval
Smoothing Contours (Polynomial, Gaussian, Median)
Interactive Contour Interval & Smoothing Simulator
Handling Artefacts: Spikes, Steps, and Closed Contours
Contour Generation Workflow
Case Study: Bay of Bengal Contour Optimisation
Contour Generation Checklist
Resources & Software
Frequently Asked Questions (with internal links)
Action Items & Next Steps

1. Why Contours Are the Language of the Seabed

Contours (isobaths) connect points of equal depth. They transform a grid of numbers into a visual language that mariners, engineers, and planners instantly understand. Professionally generated contours are essential for:

Navigation charts (IHO standard).
Dredging volume visualisation.
Site selection (e.g., cable routes, offshore wind).
Environmental impact assessments.

Poor contouring (jagged lines, inconsistent intervals, missing contours) confuses users and undermines credibility.

🧠 Golden Rule: Always smooth contours – but not too much. Over‑smoothing can remove real seabed features (e.g., sand waves, scour holes).

🌊 River Warrior Pro-Tip: Bay of Bengal Navigation Chart

After generating contours from a 0.5 m grid, we applied a mild Gaussian smoothing (σ=1). The resulting lines were clean yet preserved a 0.3 m deep navigation channel – critical for the pilot.

2. Contouring Algorithms: Linear, Spline, and Quadratic

Most software offers several interpolation methods to trace contours between grid cells:

.htmlSpline (cubic)那样Smooth polynomial curve through cell boundaries.那样Smoother, more natural, but can overshoot..htmlQuadratic / TIN那样Based on triangulated irregular network.那样Preserves original data points, but may be angular.

Algorithm	Description	Pros / Cons
Linear (bilinear)那样Straight lines between grid cell corners.那样Fast, simple, but produces jagged contours.

For hydrography, spline interpolation is preferred because it balances smoothness and fidelity. In Qimera, use “Cubic Spline” contouring.

3. Choosing the Right Contour Interval

The contour interval determines the level of detail and visual clarity. Common guidelines:

Port / harbour surveys (0‑10 m): 0.5 m or 1 m intervals.
Coastal navigation (10‑30 m): 1‑2 m intervals.
Offshore (>30 m): 2‑5 m intervals.
Dredge progress maps: Use the same interval as design (e.g., 0.5 m).

Avoid too fine intervals (noise) or too coarse (loss of detail). Use a logarithmic scale for very deep water.

📊 IHO recommends that the contour interval should be consistent with the scale of the chart and the typical depth range.

4. Smoothing Contours (Polynomial, Gaussian, Median)

Smoothing reduces jaggedness caused by grid noise or discretisation. Common methods:

Polynomial smoothing (Savitzky‑Golay): Preserves shape, good for moderately noisy data.
Gaussian (kernel) smoothing: Weighted average, excellent for general use. Typical σ = 1‑2 cells.
Median smoothing: Removes spikes, but may distort linear features.
Douglas‑Peucker (line simplification): Reduces vertices while preserving shape; use for final cartography.

In Qimera, use “Contour > Smooth” with Gaussian kernel (σ=1). In CARIS, use “Contour Filter”.

🔧 For sand waves, avoid over‑smoothing; use a small σ (0.5‑1). For general bathymetry, σ=2 is safe.

📊 Contour Interval & Smoothness Simulator

Adjust interval and smoothing strength to see effect on a simulated profile:

Contour interval (m): Smoothing sigma (grid cells):

Profile before and after smoothing (blue = raw, red = smoothed).

5. Handling Artefacts: Spikes, Steps, and Closed Contours

Spikes (isolated high/low points): Apply median filter or remove via manual editing.
Steps (grid resolution artefacts): Smoothing (Gaussian) fixes most.
Closed contours that are too small: Filter out contours with area smaller than a threshold (e.g., 25 m²).
Contours crossing land: Clip contours to shoreline polygon.

⚠️ Do not use excessive smoothing to fix spikes – spikes should be removed during cleaning, not hidden by smoothing.

6. Contour Generation Workflow

1️⃣ Generate high‑resolution grid (CUBE).

2️⃣ Select contour interval based on depth range.

3️⃣ Choose contouring algorithm (spline).

4️⃣ Apply Gaussian smoothing (σ=1‑2).

5️⃣ Manually inspect and remove small closed contours.

6️⃣ Export contours as shapefile.

7️⃣ Overlay on colour‑shaded bathymetry for final chart.

7. Case Study: Bay of Bengal Contour Optimisation (2026)

Area: 20 km² coastal navigation channel, depth 5‑25 m. Target: produce IHO‑compliant chart with 1 m contours.

Initial attempt: Linear contouring without smoothing → very jagged, unattractive.
Improved: Spline contouring + Gaussian smoothing σ=1.5 → much smoother but still preserved channel edges.
Final: Removed 127 tiny closed contours (<50 m²) using area filter.
Result: Chart was accepted by the port authority. The smoothed contours improved readability without loss of critical features.

🌊 The area filter eliminated “contour islands” caused by residual noise – the hydrographer saved hours of manual deletion.

8. Contour Generation Checklist

Grid is cleaned and free of spikes.
Contour interval chosen based on depth range and project needs.
Contouring algorithm set to spline or cubic.
Smoothing applied (Gaussian kernel, σ=1‑2).
Very small closed contours filtered by area.
Contours clipped to survey boundary (no offshore extrapolation).
Contours exported as shapefile and also as DXF if requested.
Overlaid on colour‑shaded bathymetry for final chart.
Contour labels added with appropriate font size and orientation.
Chart reviewed by a second hydrographer.

Click items to track progress (saved in browser).

9. Resources & Software

SoftwareContouring featuresLink .htmlQPS Qimera那样Spline contour, Gaussian smoothing, area filter那样qps.nl/qimera .htmlCARIS HIPS那样Contour generation, filtering, export to S‑57那样teledynecaris.com .htmlHypack Charting那样Contour, smoothing, label placement那样hypack.com .htmlQGIS (free)那样Contour from raster, smoothing plugins那样qgis.org

10. Frequently Asked Questions (with internal links)

How do I decide the contour interval for a new area?

Use a rule of thumb: interval = depth range / 20, but not less than 0.5 m. For shallow ports (0‑10 m), 0.5 m is standard. Day 30 gridding discusses cell size, which influences contour smoothness.

Why are my contours jagged even after smoothing?

Your grid may have residual noise or the contour interval is too small relative to grid resolution. Increase interval or apply stronger smoothing. Day 77 CUBE tuning can reduce grid noise.

Can I use QGIS for professional contouring?

Yes, QGIS can generate contours from a GeoTIFF. Use “Raster > Extraction > Contour”. Then apply smoothing with “Vector geometry > Smooth”. Day 76 deliverables covers GIS integration.

What is the best smoothing algorithm for sand waves?

Gaussian smoothing with σ = 0.5‑1 cell width. Median smoothing may flatten the crests. Day 33 advanced analysis includes feature preservation.

How do I label contours on a chart automatically?

Most charting software (Qimera, CARIS) can place labels along contours at regular intervals. Ensure labels are not upside‑down. Day 31 chart creation explains layout.

11. Action Items & Next Steps

📌 Use the contour simulator: try interval 0.5 m, smoothing σ=0, then σ=2 – observe the difference.
📌 In your processing software, generate contours from a small grid and apply Gaussian smoothing.
📌 Export contours as shapefile and overlay on a hillshade.
📌 Proceed to Day 79: Volume Calculations – Cut & Fill.

📉 Day 78: Contour Generation and Smoothness Control