Uganda Food Security Map

Interactive visualization of food security metrics, weather patterns, and agricultural insights across Uganda

Kampala

Low Risk

Central Region

Food Security Score85

Wakiso

Low Risk

Central Region

Food Security Score78

Mukono

Medium Risk

Central Region

Food Security Score72

Mbarara

Medium Risk

Western Region

Food Security Score65

Gulu

High Risk

Northern Region

Food Security Score52

Lira

High Risk

Northern Region

Food Security Score48

Jinja

Medium Risk

Eastern Region

Food Security Score70

Mbale

Medium Risk

Eastern Region

Food Security Score68

Fort Portal

Low Risk

Western Region

Food Security Score74

Masaka

Low Risk

Central Region

Food Security Score76

Arua

High Risk

West Nile Region

Food Security Score55

Soroti

High Risk

Eastern Region

Food Security Score58

Hoima

Medium Risk

Western Region

Food Security Score64

Kabale

Medium Risk

Western Region

Food Security Score71

Kasese

Medium Risk

Western Region

Food Security Score62

Tororo

Medium Risk

Eastern Region

Food Security Score66

Mubende

Medium Risk

Central Region

Food Security Score69

Kitgum

High Risk

Northern Region

Food Security Score50

Bushenyi

Low Risk

Western Region

Food Security Score73

Iganga

Medium Risk

Eastern Region

Food Security Score67

Nebbi

High Risk

West Nile Region

Food Security Score54

Data Sources & Methodology

Food Security Scores

Food security scores are derived from multi-modal machine learning models analyzing:

  • Uganda Bureau of Statistics (UBOS) agricultural census data
  • World Food Programme (WFP) Vulnerability Analysis and Mapping
  • FAO Food Security Indicators
  • Farm Zenith field research data from Mbarara and surrounding districts

Weather & Climate Data

Weather and climate metrics are sourced from:

  • OpenWeatherMap API (real-time weather data)
  • Uganda National Meteorological Authority (UNMA)
  • NASA POWER Data Access Viewer (historical climate data)
  • Copernicus Climate Change Service (C3S)

Note: Food security scores are predictive indicators based on historical data, current conditions, and machine learning models. Scores are updated quarterly and should be used as guidance alongside local knowledge and ground-truth assessments.