Published May 29, 2026
| Version v1
Software documentation
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Codes Used for analysis
Authors/Creators
Description
This contains all the code developed and used for the analysis in this thesis. This script uses absolute file paths specific to the author's machine. Before running, update all path variables in the configuration section to match your local directory structure. Input datasets (commodity prices, demand and supply elasticities, LUTO2 baseline layers, and scenario definitions) are referenced by location rather than embedded. When reusing this code on a different system or applying it to a new analysis, verify that every input path resolves correctly and that the input data are up to date, as the outputs depend on the versions supplied at run time.
Notes
For the Area Matrix code, this part has been added later:
records = []
records = []
for (ssp, diet, prod), mat in results.items():
mat_np = mat.values.copy()
np.fill_diagonal(mat_np, 0)
total_change = np.abs(mat_np).sum() / 1e6 # convert to Mha
records.append({
'SSP': SSP_LABELS[ssp],
'Diet': DIET_LABELS[diet],
'Productivity': PROD_LABELS[prod],
'Total Area Changed (Mha)': round(total_change, 3)
})
df_table = (pd.DataFrame(records)
.sort_values(['SSP', 'Diet', 'Productivity'])
.reset_index(drop=True))
df_table.to_csv("land_use_change_2050_Mha.csv", index=False)
print(df_table.to_string(index=False))
save_path = "land_use_change_2050_Mha.csv"
print(f"Saved summary table to {save_path}")
Files
area matrix LUTO2.ipynb
Files
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