config.yaml

# ClimateVision Configuration
# Multi-Climate Analysis Platform

# ===== Analysis Types Configuration =====
# Each analysis type can be enabled/disabled and configured independently
analysis_types:
  # Deforestation Detection
  deforestation:
    enabled: true
    display_name: "Deforestation Detection"
    description: "Monitor forest coverage and detect deforestation events"
    model:
      architecture: "unet"
      weights: "models/unet_deforestation.pth"
      in_channels: 4
      num_classes: 2
    bands: ["B04", "B03", "B02", "B08"]  # Red, Green, Blue, NIR
    classes: ["non_forest", "forest"]
    thresholds:
      alert_forest_loss: 5.0        # Alert if >5% forest loss
      critical_forest_loss: 15.0    # Critical if >15% loss
      min_forest_coverage: 20.0     # Alert if coverage drops below 20%
    metrics:
      - "forest_percentage"
      - "forest_pixels"
      - "ndvi_stats"
      - "carbon_estimation"

  # Arctic Ice Melting
  ice_melting:
    enabled: true
    display_name: "Arctic Ice Melting"
    description: "Monitor sea ice extent and melting patterns in polar regions"
    model:
      architecture: "unet"
      weights: "models/unet_ice.pth"
      in_channels: 4
      num_classes: 3
    bands: ["B02", "B03", "B04", "B11"]  # Blue, Green, Red, SWIR
    classes: ["open_water", "sea_ice", "land"]
    thresholds:
      alert_ice_loss: 10.0          # Alert if >10% ice loss
      critical_ice_loss: 25.0       # Critical if >25% loss
      min_ice_concentration: 15.0   # Alert if concentration below 15%
      rapid_melt_rate: 5.0          # km²/day threshold
    metrics:
      - "ice_percentage"
      - "ice_extent_km2"
      - "melt_rate"
      - "ndsi_stats"
    # Specific regions for Arctic monitoring
    default_regions:
      arctic_ocean: [-180, 66.5, 180, 90]
      greenland: [-73, 60, -12, 84]
      antarctica: [-180, -90, 180, -60]

  # Flood Detection
  flooding:
    enabled: true
    display_name: "Flood Detection"
    description: "Detect and monitor flooding events and affected areas"
    model:
      architecture: "unet"
      weights: "models/unet_flood.pth"
      in_channels: 3
      num_classes: 3
    bands: ["B03", "B08", "B11"]  # Green, NIR, SWIR
    classes: ["dry_land", "permanent_water", "flooded"]
    thresholds:
      alert_flood_area: 5.0         # Alert if >5% area flooded
      critical_flood_area: 20.0     # Critical if >20% flooded
      rapid_expansion_rate: 10.0    # % increase per day
    metrics:
      - "flooded_percentage"
      - "flooded_area_km2"
      - "mndwi_stats"

  # Drought Monitoring
  drought:
    enabled: false  # Not yet implemented
    display_name: "Drought Monitoring"
    description: "Monitor vegetation stress and drought conditions"
    model:
      architecture: "unet"
      weights: "models/unet_drought.pth"
      in_channels: 4
      num_classes: 4
    bands: ["B04", "B08", "B11", "B12"]  # Red, NIR, SWIR-1, SWIR-2
    classes: ["normal", "mild_stress", "moderate_stress", "severe_drought"]
    thresholds:
      alert_drought_index: 0.3
      critical_drought_index: 0.6
    metrics:
      - "drought_severity_index"
      - "vegetation_health_index"
      - "soil_moisture_proxy"

  # Wildfire Detection
  wildfire:
    enabled: false  # Not yet implemented
    display_name: "Wildfire Detection"
    description: "Detect active fires and burned areas"
    model:
      architecture: "unet"
      weights: "models/unet_wildfire.pth"
      in_channels: 4
      num_classes: 3
    bands: ["B04", "B08", "B11", "B12"]  # Red, NIR, SWIR-1, SWIR-2
    classes: ["unburned", "burned", "active_fire"]
    thresholds:
      fire_radiative_power: 10.0    # MW
      burned_area_alert: 1.0        # km²
    metrics:
      - "burned_area_km2"
      - "fire_intensity"
      - "nbr_stats"  # Normalized Burn Ratio

# ===== Default Model Configuration =====
model:
  architecture: "unet"
  in_channels: 4  # RGB + NIR
  num_classes: 2  # forest / non-forest
  use_uncertainty: false
  dropout_rate: 0.5

# ===== Training Configuration =====
training:
  batch_size: 8
  num_epochs: 50
  learning_rate: 0.0001
  optimizer: "adam"
  loss_function: "combined"  # focal, dice, or combined
  focal_weight: 0.5
  checkpoint_interval: 5
  early_stopping_patience: 10

# ===== Data Configuration =====
data:
  image_size: [256, 256]
  bands: ["Red", "Green", "Blue", "NIR"]
  normalization: "minmax"  # minmax or standardize
  augmentation: true
  train_split: 0.8
  val_split: 0.1
  test_split: 0.1

# ===== Satellite Data Sources =====
satellite:
  sentinel2:
    bands: ["B04", "B03", "B02", "B08"]  # Red, Green, Blue, NIR
    all_bands: ["B01", "B02", "B03", "B04", "B05", "B06", "B07", "B08", "B8A", "B09", "B10", "B11", "B12"]
    resolution: 10  # meters
    cloud_coverage_max: 20  # percentage
    revisit_time: 5  # days
  
  landsat8:
    bands: ["B4", "B3", "B2", "B5"]
    resolution: 30  # meters
    revisit_time: 16  # days
  
  modis:
    bands: ["1", "2", "3", "4", "5", "6", "7"]
    resolution: 250  # meters (bands 1-2), 500m (3-7)
    revisit_time: 1  # days
    use_for: ["ice_melting", "wildfire"]  # Best for large-scale monitoring

# ===== Inference Configuration =====
inference:
  batch_size: 4
  threshold: 0.5
  tile_size: [256, 256]
  overlap: 32
  device: "cuda"  # cuda or cpu
  num_workers: 4

# ===== MLOps Configuration =====
mlops:
  experiment_tracking: "mlflow"  # mlflow, wandb, or none
  model_registry: "mlflow"
  logging_interval: 10  # log every N batches
  
# ===== Paths =====
paths:
  data_dir: "data/"
  models_dir: "models/"
  logs_dir: "logs/"
  outputs_dir: "outputs/"

# ===== API Configuration =====
api:
  host: "0.0.0.0"
  port: 8000
  workers: 4
  timeout: 60
  max_file_size: 100  # MB
  cors_origins:
    - "http://localhost:5173"
    - "http://localhost:3000"

# ===== Organization (NGO) Configuration =====
organizations:
  enable_registration: true
  require_email_verification: false
  default_alert_channels: ["email"]
  max_subscriptions_per_org: 10
  api_rate_limit: 100  # requests per minute