Bherney/Spatio-Temporal-Assessment-of-Climate-Change-Impact-on-Cereal-Crop-Yields-in-Nigeria-using-Python

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. --- ## 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 🌍 --- ## 📂 Repository Structure - **plots/** → All generated plots (boxplots, maps, bar chart) - **script/** → Python scripts for analysis - **data/** → CSV and shapefiles - **README.md** → Project documentation --- ## 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 --- ## 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 …