[Python] How to Automate Earthwork Cut/Fill Calculations for Irregular Terrain Using Python?

I'm managing a construction project where we need to calculate cut/fill volumes between existing ground levels and proposed design levels. The site has irregular topography (varying slopes, drainage channels), and we're using a 20m × 20m grid for measurements.

Current Manual Process: Surveyors collect spot levels at grid intersections.

For each grid cell, calculate average existing vs. proposed elevation.

Compute volume per cell: Volume = Area × (Avg. Existing Elevation - Avg. Proposed Elevation).

Sum cut/fill volumes separately.

Problem:

Manual calculations for 500+ grid cells are time-consuming and error-prone. I need a Python script to:

1. 
   Import survey data from CSV (columns: Grid_ID, X, Y, Existing_Z, Proposed_Z).
   
   
2. 
   Auto-identify cut/fill per cell (positive = fill, negative = cut).
   

Handle edge cases:

• Partial cells at site boundaries (triangles/trapezoids).
• Cells where cut/fill transitions occur (e.g., half-cut/half-fill).
• Output total cut/fill volumes and a heatmap visualization.

Attempted Solution (Partial Code):

import pandas as pd


data = pd.read_csv("survey_data.csv")

Calculate average elevation per cell?


data["Volume"] = data["Area"] * (data["Proposed_Z"] - data["Existing_Z"])

But how to handle irregular cells and cut/fill transitions?

But how to handle irregular cells and cut/fill transitions?


Specific Questions:

1. Algorithm: What’s the most efficient way to compute cell-level volumes for irregular grids?
2. Cut/Fill Transition: How to split cells where cut and fill coexist (e.g., using linear interpolation)?
3. Visualization: Any Python libraries (e.g., matplotlib, plotly) to generate a cut/fill heatmap like the diagram?

Sample Data:

Grid_ID X Y Existing_Z Proposed_Z A1 0 0 102.3 103.5 A2 20 0 101.7 102.8 ... ... ... ... ...

Desired Output:

• Total Cut Volume: 15,200 m³
• Total Fill Volume: 12,800 m³
• Heatmap showing cut/fill intensity across the site.

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