GEO-INFER-AG

Instructions

Core Capabilities

• Soil health: USDA soil data integration, nutrient modeling
• Carbon sequestration: IPCC Tier 1 methodology for agricultural carbon
• Water usage: FAO-56 crop-specific water productivity calculations
• Precision farming: Variable rate application, yield prediction
• Land management: Crop rotation optimization, field boundary analysis

Key Imports

from geo_infer_ag.models.soil_health import SoilHealthModel
from geo_infer_ag.models.carbon_sequestration import CarbonSequestrationModel
from geo_infer_ag.models.water_usage import WaterUsageModel

Examples

from geo_infer_ag.models.water_usage import WaterUsageModel

model = WaterUsageModel(crop="maize", climate_zone="temperate")
daily_water = model.compute_daily_requirement(
    eto=5.2,  # reference evapotranspiration (mm/day)
    growth_stage="mid_season"
)
print(f"Crop water need: {daily_water:.1f} mm/day")
seasonal = model.seasonal_demand(planting_date="2026-04-15")

from geo_infer_ag.models.carbon_sequestration import CarbonSequestrationModel

carbon = CarbonSequestrationModel(method="ipcc_tier1")
result = carbon.estimate(
    land_area_ha=100,
    soil_type="clay_loam",
    management="no_till"
)
print(f"Annual sequestration: {result.tonnes_co2_per_year:.1f} t CO₂/yr")

Guidelines

• Soil models use USDA data (not random values)
• Carbon uses IPCC Tier 1 methodology
• Water productivity uses FAO-56 crop-specific defaults
• Test: uv run python -m pytest GEO-INFER-AG/tests/ -v

Integrations

• CLIMATE → Precipitation projections for irrigation planning
• WATER → Irrigation water demand modeling
• SPACE → H3-based field tessellation and precision farming grids
• RISK → Crop loss risk assessment
• ECON → Agricultural market pricing and supply chain