Environmental Sustainability Dashboard

Repository Structure

• datasets/ → CSV/Excel datasets used
• .pbix_file/ → Power BI report files
• .png/ → Screenshots of dashboards and insight notes

Project Goals

• Apply analytics to real-world sustainability datasets

Day 1 – Urban Farming

• Designed and generated a sample dataset: Urban_Farming.csv
• Imported data into Power BI and explored the interface
• Built a basic visualization and insights dashboard (day1_visualization.png and day1_insights.png)
• Focus: city-level crop yields and production patterns

Day 2 – Tree Planting Analysis

• Developed a star schema with fact and dimension tables (Cities, Species, Tree_Planting)
• Created key DAX measures (Total Trees, Avg Trees per Planting, CO₂ Absorption Estimate, % by Species)
• Designed an interactive dashboard with region, city, and species breakdowns
• Key Insight: Southwest region & Port Harcourt lead in planting efforts.

Day 3 – Climate & Agriculture Yield

• Standardized and cleaned datasets.
• Modeled data into a star schema with fact and dimension tables.
• Created DAX measures for average rainfall, average temperature, total yield, and event-adjusted yield.
• Built visualizations to highlight climate trends, yield distribution, and correlations.

The focus for Day 3 was not only on building the dashboard but also on Data Storytelling: translating visuals into meaningful insights.

Day 3 insights.

Agricultural yields are heavily influenced by climate — rainfall, temperature, and extreme events. This dashboard explores how climate patterns over the past decade have shaped agricultural yields across regions. The goal was to examine whether shifts in climate patterns are correlated with changes in crop productivity.

Key Visuals & Insights

1. Climate Trends Over Time

Area Chart – Rising average temperatures alongside declining rainfall.

• A brief rainfall spike appears in 2018, but the long-term trend points downward.
• Temperatures climb steadily, signaling a hotter, drier climate.
  Impact: Farmers face less water and more heat, both of which threaten stable food production.

2. Crop Yield Leaders

Ribbon Chart – Cereals consistently dominate yields, followed by legumes and root/tuber crops.

• Yield levels fluctuate in response to rainfall and temperature shifts.
  Impact: Cereals remain resilient, but legumes (which need stable rainfall) show higher vulnerability.

3. Rainfall vs Yield

Scatter Plot – A positive correlation emerges: as rainfall increases, yields rise. The regression line slopes upward, showing that water availability directly supports food output.

• Rainfall above ~1100 mm tends to push yields closer to 150K.
• Lower rainfall years cluster around 135K–140K yields.

4. Temperature vs Yield

Scatter Plot – A negative correlation is clear: The downward-sloping regression line shows that higher temperatures lead to lower yields.

• Once average temperatures cross 228–230°C, yields consistently fall below 140K.

5. Extreme Events & Yield Performance

Column-Line Combo Chart – The effect of droughts, floods, and heatwaves.

• Yields dip sharply during drought years.
• Rainfall fluctuations add another layer of instability.
  Impact: Farmers aren’t just battling averages — it’s the spikes and shocks that devastate harvests.

Conclusion

• Rainfall strongly supports yield growth.
• Rising temperatures undermine food security.
• Extreme events intensify risks, driving volatility in farming outcomes.
• Cereals dominate yields but climate pressures may challenge this resilience over time.