Mapping 600+ agricultural trial locations on one interactive map

Using Leaflet inside R Shiny to map 600+ maize trial locations with yield colour-coding and district filters — and why ‘where’ matters as much as ‘what’.
GIS
R Shiny
Agricultural Analytics
Case Study
Author

Victor Mandela

Published

14 September 2026

Keywords

agricultural analytics, R Shiny dashboard, maize yield, Rwanda, gis, r shiny

Open to roles & consulting · M&E · Impact Evaluation · Agricultural Analytics · R Shiny LinkedInGitHubEmailBook a call
Victor Mandela, M&E and data science consultant
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Portfolio Edition ••• Monitoring & Evaluation · Impact Evaluation · R Shiny Decision Support ••• Nairobi, KenyaUPDATED NOV 2026

The maize yield Shiny application includes a Leaflet map showing:

Mapping 600+ agricultural trial locations on one interactive map — infographic

Why does this matter?

Agricultural data is rarely just about what happened. It’s also about where. Two farmers can apply the same treatment and get very different results because of soil, rainfall, location and agro-ecological environment.

Collapse all of that into a national average and the variation isn’t resolved — it’s hidden.

An underrated benefit

A map shows you very quickly where your evidence actually is — and where you’re extrapolating from thin coverage.

This is why I keep combining Statistics + GIS + R + Shiny.

▶ Try it yourself — live R Shiny demo. Open the Rwanda Maize Yield Analyzer · Username: test · Password: test

Part 5 of 10 — The Maize Yield Case Study. Read the full case study and launch the dashboard › · Work with me on a similar project ›