Bherney/Spatio-Temporal-Assessment-of-Climate-Change-Impact-on-Cereal-Crop-Yields-in-Nigeria-using-Python
Domaine:
agricultureclimateType de record:
project
Créateur:
Bhe
Hôte:
The study evaluated the projected impacts of climate change on cereal crop yields in Nigeria under two contrasting climate pathways-SSP3-7.0 (medium emissions) and SSP5-8.5 (high emissions) for the periods 2021–2040 and 2041–2060.
# Spatio-Temporal Assessment of Climate Change Impact on Cereal Crop Yields in Nigeria (Python)
This repository contains the analysis and visualization scripts for assessing the **impact of climate change on cereal crop yields (maize, sorghum, millet, wheat) across Nigerian states** under two climate scenarios:
- **SSP3-7.0 (medium emissions)**
- **SSP5-8.5 (high emissions)**
The study evaluates yield projections for two future periods (**2021–2040** and **2041–2060**), compares state-level vulnerabilities, and identifies priority states for adaptation investments.
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## Study Overview
- **Objective 1:** Analyze spatial variations in projected cereal yields under SSP3-7.0 and SSP5-8.5.
- **Objective 2:** Compare vulnerability of Nigerian states to yield reductions across crops.
- **Objective 3:** Determine priority states for climate adaptation by evaluating yield gaps between scenarios.
**Data Source:** CGIAR Adaptation Atlas 🌍
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## 📂 Repository Structure
- **plots/** → All generated plots (boxplots, maps, bar chart)
- **script/** → Python scripts for analysis
- **data/** → CSV and shapefiles
- **README.md** → Project documentation
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## Methodology
1. **Data Extraction**: Cereal yield data collected from CGIAR Adaptation Atlas for Nigeria’s 36 states + FCT.
2. **Scenario Analysis**: Compared SSP3-7.0 vs SSP5-8.5 for two periods (2021–2040, 2041–2060).
3. **Python Workflow**:
- Data cleaning & structuring with **Pandas**
- Statistical summaries, barchart & boxplot with **Seaborn/Matplotlib**
- Yield gap analysis with **NumPy**
- Spatial visualization using **GeoPandas** & choropleth maps
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## Key Results (Highlights)
- **Highest negative yield gaps**: Plateau (−0.39), FCT (−0.36), Akwa Ibom (−0.33).
- **Positive yield gaps (resilient states)**: Adamawa (+0.18), Yobe (+0.11), Jigawa (+0.08).
- **Southwest states** (Oyo, Ondo, Osun, Ekiti) show moderate declines (−0.13 to −0.14), signaling emerging vulnerability.
- Millet and sorghum in northern st …
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