Machine learning and statistical models for land-use carbon accounting and emissions analysis in Tanzania.
# Land Use Change and CO₂ Emissions Modeling in Tanzania
## Project Overview
This repository contains MATLAB scripts, datasets, and LaTeX manuscript files used to analyze the relationship between **land use change and CO₂ emissions in Tanzania**.
The project applies **statistical analysis, visualization, and machine learning models** to explore how land-use transitions, population growth, and economic development influence emissions over time.
The repository also contains a **LaTeX manuscript template** used for preparing the research article.
---
# Repository Structure
```
├── Histogram.m
├── residualQQPlot.m
├── Sinariors.m
├── emissionPopulationGdp_over_time.m
├── emissions_by_landUse_Type.m
├── Correlation.R
├── Average CO2 Emissions by Land Use Type.R
├── Emissions Forecast Comparison.m
├── rf_model.R
├── LUC and Emissions data in Tanzania
├── plos_latex_template.tex
├── plos_bibtex_sample.bib
└── README.md
```
---
# Description of MATLAB Scripts
### Histogram.m
Generates histogram plots to visualize the distribution of key variables in the dataset.
### residualQQPlot.m
Creates Q-Q plots to assess whether regression residuals follow a normal distribution.
### Sinariors.m
Runs scenario simulations for different land-use change and emissions pathways.
### emissionPopulationGdp_over_time.m
Visualizes the relationship between **CO₂ emissions, population growth, and GDP** over time.
### emissions_by_landUse_Type.m
Analyzes emissions associated with different **land-use categories** such as forest, cropland, and settlements.
### Correlation.m
Computes and visualizes correlation relationships among variables including emissions, GDP, population, and land-use types.
### Average CO2 Emissions by Land Use Type.m
Calculates and visualizes the **average emissions contribution of each land-use type**.
### Emissions Forecast Comparison.m
Compares emissions predictions from different modeling approaches.
### rf_model.m
Implements a **Random Forest m …