# Core scientific stack
numpy>=1.22
pandas>=1.5
scipy>=1.8
scikit-learn>=1.1
matplotlib>=3.5
tqdm>=4.64

# Geospatial and remote sensing
rasterio>=1.3
geopandas>=0.12
shapely>=2.0
xarray>=2022.3
netCDF4>=1.6

# Visualization and mapping
cartopy>=0.21
seaborn>=0.12

# Machine learning / advanced models
scikit-optimize>=0.9
lightgbm>=3.3
xgboost>=1.7

# Utilities
joblib>=1.2
pyyaml>=6.0

# Optional: Jupyter support for reproducible workflows
notebook>=6.5
jupyterlab>=3.5