SmartCrop Lite is a geospatial agricultural decision-support system that integrates market price data, rainfall monitoring (CHIRPS-style), and soil analysis (iSDA-style) to generate localised, data-driven recommendations for smallholder farmers across Kenya.
The platform enables farmers, agronomists, and field programme teams to make informed decisions on:
- When to plant — based on rainfall anomalies vs 20-year averages
- Where to sell — based on county-level market price comparisons
- What inputs to apply — based on soil pH, fertility, and nutrient profiles
*"Built to demonstrate geospatial agricultural analytics for smallholder farmer decision-support.
- Crop price bubble map — county-level price distribution across Kenya (Plotly Mapbox)
- Rainfall anomaly map — % deviation from 20-year average by county and month
- Soil fertility map — county soil fertility and pH distribution
- Price trend analysis over time (county + crop)
- Cross-county price comparison bar chart
- Automated buy/sell/hold recommendations based on price trend direction
- Monthly rainfall vs long-term average (CHIRPS-style data)
- Planting signal heatmap — county × month matrix showing Plant / Watch / Delay signals
- Automated planting window recommendation with agronomic rationale
- Soil profile: pH, texture, drainage, organic carbon, N/P/K
- Nutrient radar chart — visual soil health profile
- Lime and fertiliser recommendations (e.g., CAN, DAP application rates)
- iSDA-style soil data integration
| Layer | Tools |
|---|---|
| Frontend | Streamlit |
| Data Manipulation | Python, Pandas, NumPy |
| Geospatial | GeoPandas, Plotly Mapbox |
| Visualisation | Plotly Express, Plotly Graph Objects |
| Data Sources | CHIRPS (rainfall), iSDA Africa (soil), County market surveys |
| Version Control | Git / GitHub |
smartcrop-lite/
│── app.py # Main Streamlit application
│── requirements.txt # Dependencies
│── README.md
│── data/
│ ├── prices.csv # County crop market price data (lat/lon enabled)
│ ├── rainfall.csv # CHIRPS-style monthly rainfall + planting signals
│ └── soil.csv # iSDA-style soil profiles + input recommendations
└── images/
└── dashboard.png # Sample dashboard screenshot
https://smartcrop-lite-bjjh8evg2pyzjwnwymzmwb.streamlit.app/
---
## 📊 Data Sources & Methodology
| Dataset | Source | Description |
|---|---|---|
| Rainfall | CHIRPS (Climate Hazards Group) | Monthly precipitation, anomaly vs 20-year baseline |
| Soil | iSDA Africa | pH, N/P/K, organic carbon, soil texture by county |
| Prices | County market surveys | Weekly crop prices across major Kenyan markets |
### Planting Signal Logic
| Signal | Condition | Recommendation |
|---|---|---|
| ✅ PLANT | Rainfall ≥ long-term average (anomaly ≥ 0%) | Proceed — moisture conditions favourable |
| ⚠️ WATCH | Rainfall within -15% of average | Monitor — wait for further rainfall before planting |
| ❌ DELAY | Rainfall < -15% of average | Delay — high risk of crop failure under current conditions |
### Fertiliser Recommendation Logic
- Soil pH < 5.5 → Lime application (tonnes/ha) calculated before fertiliser
- N-deficient soils → Higher CAN rates recommended
- All recommendations follow Kenya Ministry of Agriculture guidelines
---
## 🎯 Use Case
Built for:
- **Smallholder farmers** — making planting and selling decisions
- **Agronomists & field officers** — county-level programme targeting
- **Agricultural R&D teams** — integrating spatial data into decision-support tools
- **Programme managers** — monitoring seasonal conditions across geographies
---
## 🌍 Impact
SmartCrop Lite v2.0 contributes to:
- 📉 Reduced crop failure risk through data-driven planting window guidance
- 💰 Increased farmer income through market arbitrage price awareness
- 🌱 Improved soil health through localised input recommendations
- 🗺️ Geospatially targeted programme design and farmer support
---
## 🔮 Roadmap
- [ ] CHIRPS API live integration (real-time rainfall data)
- [ ] iSDA Africa API integration (live soil layers)
- [ ] NDVI vegetation index integration (Sentinel-2 / Google Earth Engine)
- [ ] Sowing date optimisation model (Growing Degree Days)
- [ ] SMS alert integration for low-connectivity users
- [ ] Expansion to Uganda, Rwanda, Tanzania, Ethiopia (OAF countries of operation)
- [ ] GxE interaction modelling for variety × environment recommendations
---
## 👨💻 Author
**Evans Kiplangat** — Data Analyst | Agricultural Analytics | Geospatial Data Systems
- 🌐 [GitHub](https://github.com/evans25575)
- 💼 [LinkedIn](https://www.linkedin.com/in/evans-kiplangat-375646179)
- 📧 [email protected]
---
## 📄 License
MIT License — open for research collaboration and adaptation.
---
*SmartCrop Lite is an open-source agricultural analytics project. Data used is for demonstration purposes. For production deployment, connect live CHIRPS, iSDA, and market price API feeds.*