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Problem Statement 4

"Geospatial NPK Monitoring System"​

Focus: Nutrient Mapping | Satellite-Based Soil Analysis | Fertilizer Optimization | Precision Agriculture

1. Background:​

Soil testing labs provide NPK values, but testing is slow (7-10 days) and expensive (₹200-500/sample). Satellite data can estimate nutrient deficiencies through vegetation indices, yet farmers over-apply or under-apply fertilizers, causing cost overruns and environmental damage.

2. Current Problem:​

1. Inefficient Fertilizer Use

  • Blanket NPK application across entire fields
  • No spatial awareness of nutrient variation
  • Impact: 30-40% fertilizer waste, soil degradation

2. Delayed Soil Testing

  • Lab results come too late for timely intervention
  • Can't monitor nutrient changes during crop season
  • Impact: Miss critical growth stage windows

3. No Spatial Mapping

  • Point samples don't represent entire field
  • Can't identify nutrient deficiency zones
  • Impact: Uniform treatment of non-uniform fields

3. Goal:​

Build a system that maps NPK deficiency zones using satellite proxies and recommends optimized fertilizer doses.

Beyond soil testing → Create a platform that:

  1. Estimates nutrient stress from vegetation indices
  2. Maps deficiency zones spatially
  3. Recommends crop-specific fertilizer doses
  4. Tracks nutrient trends across growing season

4. Expected Solution (MVP Requirements):​

1. Nutrient Proxy Estimation​

Derive NPK indicators from satellites:

  • Nitrogen (N): NDVI, Chlorophyll Index
  • Phosphorus (P): Soil brightness, red-edge bands
  • Potassium (K): Vegetation stress indices
  • Correlation: Map indices to deficiency levels (low/medium/high)

Output: NPK deficiency scores per zone (0-100 scale)

2. Spatial Deficiency Mapping​

Create nutrient maps:

  • Color-Coded Zones: Green (sufficient) → Red (deficient)
  • Field Segmentation: Divide into management zones
  • Crop-Specific Thresholds: Rice vs wheat nutrient requirements

Demo Goal: Show a field with 3 distinct NPK zones requiring different treatments

3. Fertilizer Recommendation Engine​

Generate actionable advice:

  • Input: Crop type + growth stage + detected deficiency
  • Output: Recommended NPK dose (kg/hectare) per zone
  • Optimization: Reduce total fertilizer use by 20-30% vs blanket application

Validation: Compare recommended vs traditional doses, show cost savings

4. Monitoring Dashboard​

Real-time visualizations:

  • NPK Heatmaps: Separate maps for N, P, K deficiency
  • Temporal Trends: Nutrient status changes over 60 days
  • Dose Calculator: Interactive tool (crop + area → fertilizer quantity)
  • Impact Metrics:
    • Area analyzed (hectares)
    • Fertilizer savings estimated (kg, ₹)
    • Deficiency zones identified

5. "Level Up" Features:​

Advanced Features (Choose 2-3)

  • Yield Prediction: Forecast output based on NPK trends
  • Weather Integration: Adjust recommendations for rainfall/temperature
  • IoT Fusion: Combine satellite + ground sensor data for accuracy
  • Multi-Crop Support: Handle 5+ crops with specific nutrient curves
  • Variable Rate Maps: Export prescription maps for smart sprayers

6. Tech Stack:​

Core

  • Backend: Node.js/Express + Python/FastAPI (ML models)
  • Database: MongoDB (field data) + PostGIS (spatial)

Geospatial

  • Processing: Google Earth Engine or rasterio
  • Analysis: Scikit-learn (NPK correlation models)
  • Visualization: Leaflet.js, Mapbox GL

Frontend

  • Framework: React.js
  • Charts: Recharts, D3.js

External APIs

  • Copernicus Dataspace (Sentinel-2), USGS (Landsat), crop-specific NPK guidelines (ICAR/state agriculture departments)