import rioxarray import numpy as np def calculate_ndvi(corrected_raster_path: str) -> rioxarray.xarray_models.DataArray: """ Loads an array dataset corrected by Sen3DKol and calculates a surface health index. """ # Open the multi-band surface reflectance dataset satellite_dataset = rioxarray.open_rasterio(corrected_raster_path) # Isolate individual spectral arrays (Assuming Band 3 is Red and Band 4 is NIR) red_band = satellite_dataset.sel(band=3).astype(np.float32) nir_band = satellite_dataset.sel(band=4).astype(np.float32) # Suppress runtime divide-by-zero warnings over empty data voids with np.errstate(divide='ignore', invalid='ignore'): ndvi = (nir_band - red_band) / (nir_band + red_band) return ndvi Use code with caution. Best Practices for Scaling Pipelines
Developing Geospatial Pipelines: Python Integration with Sen3DKol Software python sen3dkol software
The script below demonstrates how to discover raw ingestion directories, pass runtime parameters to the Sen3DKol engine, and handle operational logging: python sen3dkol software
The combination of SEN3DKOL software and Python offers several advantages: python sen3dkol software