FieldMap: Geographic intelligence for crop-specific farming decisions
FieldMap is the geographic intelligence layer in FildraAI. It provides location-aware agricultural context — covering specific countries in Africa and Asia — by integrating weather data, climate patterns, and regional crop knowledge into the broader decision-support system.
What is FieldMap?
FieldMap is the geographic intelligence layer that gives FildraAI its sense of place. It connects a user's location — down to the district level — to agricultural knowledge that is relevant to that specific context: the local crop calendar, the prevailing season, typical pest and disease risks for the area, and current weather conditions.
Rather than offering generic global guidance, FieldMap is built around the reality that farming is deeply local. A question about maize management in western Kenya has a different answer than the same question asked in central Taiwan or northern Tanzania. FieldMap exists to make that distinction meaningful inside FildraAI.
Key principle
FieldMap provides location-grounded context, not global coverage. Its geographic knowledge is specific to supported countries and regions — this is intentional, not a gap to be filled with generic answers.
Geographic coverage
FieldMap has structured geographic knowledge for a specific set of countries. Coverage is not global — it is concentrated in the regions where FildraAI's core crops (maize and rice) are most relevant and where the system has been designed to provide trustworthy guidance.
Africa
Kenya, Tanzania, Uganda, Rwanda, Ethiopia, Zambia, Zimbabwe, Malawi, Mozambique, Ghana, Nigeria. Coverage includes country, region, and district-level agricultural context for maize and rice.
Asia
Taiwan, Vietnam, Thailand, Philippines, Indonesia, Myanmar, Cambodia. Coverage focuses on rice-growing regions and includes seasonal, agroclimatic, and crop-stage context.
Outside covered regions
For locations outside the covered countries, FieldMap will still accept coordinate input and provide weather data via external APIs, but crop-specific regional guidance and agricultural context will not be available at the same level of detail. The system will indicate when operating outside its structured geographic knowledge.
How FieldMap works
FieldMap operates as a context-enrichment layer that feeds into other FildraAI components, particularly FieldGuide. When a user provides or confirms a location, FieldMap resolves that location into a structured set of agricultural signals.
Location resolution
Resolves GPS coordinates or named places to country, region, and district level. This geographic anchor is used to retrieve the correct agricultural context for that area.
Weather integration
Integrates current conditions, short-range forecasts, and historical climate baselines via external weather APIs. This data is attached to the location context so that crop guidance reflects real environmental conditions.
Regional crop knowledge
Structured knowledge about what crops are grown where, typical planting calendars by region, seasonal patterns, and common pest and disease risks by agroecological zone. This knowledge is specific to supported countries.
Context handoff to FieldGuide
The resolved geographic and weather context is passed to FieldGuide, which uses it to shape crop advice grounded in the user's actual location and season.
How to use the map
FieldMap is used primarily as a background component — it enriches context automatically when location is available. However, users can also interact with it directly to set or confirm their field location.
Setting your location
- Share GPS coordinates directly from the field
- Type a district, region, or country name
- Confirm or correct a location suggested by the system
What changes with location context
- Crop calendar and planting window recommendations become region-specific
- Pest and disease risk guidance reflects local agroecological patterns
- Weather conditions are tied to the actual field location
- Seasonal interpretation reflects the local agricultural calendar
Limitations
FieldMap is honest about what it does and does not cover. These boundaries are intentional — they reflect where structured, trustworthy agricultural knowledge exists in the system.
FieldMap can
- Provide district-level agricultural context for supported countries
- Integrate real-time and forecast weather data via external APIs
- Resolve location to country, region, and district for supported geographies
- Feed location and weather context into crop guidance components
FieldMap cannot
- Provide the same depth of regional crop knowledge outside supported countries
- Generate precise weather data independently — it relies on external API feeds
- Replace locally gathered soil or microclimate data from the specific field
- Guarantee accuracy for highly localised microclimates within a district
- Cover every country or every crop with equal depth in the current phase
Getting started
Location context is most useful when provided early in a session. The more precisely a user's location is known, the more relevant and grounded the agricultural guidance becomes.