Add Ag Forecasting application with open Lambda

Author: mariaob1201

applications/ag-forecasting-api.md

@@ -6,128 +6,8 @@ FastAPI-based ASGI service for crop disease risk forecasting using multi-source
 
 ## Overview
 
-The API provides geospatial agricultural intelligence for Wisconsin, combining weather data with validated agronomic models.
+The API provides geospatial agricultural intelligence for Wisconsin, combining weather data with validated crop disease forecasting models.
 
-### Key Features
-- 🌽 Crop disease risk forecasting (corn & soybean)
-- 🌱 Winter rye biomass estimation
-- 🌦 Multi-source weather integration (IBM EIS, WiscoNet)
-- 📍 Coordinate and station-based queries
-- 🗺 GeoJSON outputs for GIS applications
-- ⚡ Async batch processing for multi-station analysis
-
----
-
-## System Architecture
-
-The system is structured into four main layers:
-
-- **API Layer (FastAPI)**  
-  Handles incoming requests and routing (`/ibm`, `/wisconet_g`, `/models`)
-
-- **Data Layer**  
-  - IBM EIS: high-resolution global weather API  
-  - WiscoNet: Wisconsin mesonet station network  
-
-- **Processing Layer**  
-  Weather normalization, unit conversion, GDD calculation, rolling features
-
-- **Model Layer**  
-  Disease risk models and winter rye biomass model
-
----
-
-## Core Modules
-
-- Weather ingestion (IBM + WiscoNet)
-- Disease risk modeling
-- Winter rye biomass estimation
-- Async pipeline orchestration
-- GeoJSON response formatting
-
----
-
-## API Endpoints
-
-### IBM Forecasting (Coordinates)
-`GET /v2/ag_models_wrappers/ibm`
-
-Returns disease risk + biomass using IBM weather data.
-
----
-
-### WiscoNet Forecasting (Stations)
-`GET /v2/ag_models_wrappers/wisconet_g`
-
-Returns station-based time-series disease risk and biomass.
-
----
-
-### Model Metadata
-`GET /v2/ag_models_wrappers/models`
-
-Returns available disease and biomass models.
-
----
-
-## Disease Models
-
-- **Tarspot (corn)** – humidity and temperature-based risk
-- **Gray Leaf Spot (corn)** – temperature + dew point model
-- **Frogeye Leaf Spot (soybean)** – GDD + rainfall model
-- **White Mold (soybean)** – precipitation and soil moisture model
-
----
-
-## Winter Rye Biomass Model
-
-Predicts dry biomass (lb/acre) using:
-
-- Growing Degree Days (0°C base)
-- Planting date (day-of-year)
-- Fall precipitation
-- Logistic growth curve
-
-### Outputs
-- Biomass (lb/acre)
-- Color class (gray / yellow / green)
-- Interpretation message
-
----
-
-## Data Sources
-
-### IBM Environmental Intelligence Suite (EIS)
-- High-resolution global weather data
-- Hourly forecasts and historical data
-- Requires authentication
-
-### WiscoNet
-- Wisconsin mesonet (~100 stations)
-- Daily weather observations
-- Public API access
-
----
-
-## Response Format
-
-All outputs are returned as **GeoJSON FeatureCollections**, including:
-
-- Weather variables
-- Disease risk scores
-- Biomass predictions
-- Station metadata
-
----
-
-## Performance Features
-
-- Async multi-station processing
-- Cached weather and station data (6h–7d TTL)
-- Parallel risk computation
-- Optimized data aggregation pipeline
-
----
 
 ## Setup