sataid 1.0.1

A Python package for reading and visualizing SATAID binary satellite data (Himawari, etc.).

SATAID

A Python package for reading and visualizing SATAID binary satellite data files (Himawari-8/9).

Features

• 📖 Read SATAID binary files (.Z* format) and SZDD-compressed WIS files
• 🗺️ Visualize with Cartopy geographic projections
• 🎨 Built-in custom colormaps: EH, SW, WE, IR_GOES
• ✂️ Subset data by lat/lon bounding box or point extraction
• 💾 Export to NetCDF4, GeoTIFF, and xarray

Installation

pip install sataid

For optional features:

pip install sataid[all]  # Includes netCDF4, rasterio, xarray, scipy

Quick Start

Reading Data

import sataid

# Read a SATAID file
sat = sataid.read_sataid("H09_B13_Indonesia_20251126.Z0700")

# View metadata
sat.description()

Output:

=== Data Description ===
Time: 2025-11-26 07:00 UTC
Channel: L2
Dimension: 3000x2000
Resolution: 0.02
Units: °C

=== Satellite Description ===
Satellite: Himawari-9
Nadir Coordinate: -0.025393, 140.787445
Altitude: 42163.33 km

Visualization

# Simple plot with Cartopy
sat.plot()

# With custom colormap
sat.plot(cmap='IR_GOES')  # GOES-16 style
sat.plot(cmap='EH')       # BMKG Enhanced IR
sat.plot(cmap='SW')       # Sandwitch 
sat.plot(cmap='WE')       # Water Vapor enhancement

# Save to file
sat.savefig("output.png", cmap='EH')

Available Colormaps

Colormap	Description	Best For
IR_GOES	GOES-16 style infrared	IR channels (B13, B14, etc.)
EH	BMKG Enhanced IR	Cloud top temperature
SW	Sandwitch gradient	IR channels
WE	Water Vapor enhancement	WV channels (B08, B09, B10)

Subsetting Data

# Extract a region
subset = sat.sel(
    latitude=slice(-10, 0),
    longitude=slice(100, 120)
)
subset.plot()

# Extract a single point
value = sat.sel(latitude=-6.2, longitude=106.8)
print(f"Temperature: {value}°C")

# With interpolation
value = sat.sel(latitude=-6.2, longitude=106.8, method='linear')

Export Data

# To NetCDF4 (requires netCDF4)
sat.to_netcdf("output.nc")

# To GeoTIFF (requires rasterio)
sat.to_geotiff("output.tif")

# To xarray DataArray (requires xarray)
da = sat.to_xarray()

# Back to SATAID format
sat.to_sataid("output.sataid")

Access Raw Arrays

lat, lon, data = sat.to_array()

# Or directly
print(sat.lat)   # 1D latitude array
print(sat.lon)   # 1D longitude array
print(sat.data)  # 2D data array

API Reference

sataid.read_sataid(filename)

Read a SATAID binary file and return a SataidArray object.

Parameters:

• filename (str): Path to SATAID file (.Z* or .wis)

Returns:

• SataidArray: Object containing data and metadata

SataidArray Methods

Method	Description
.description()	Print formatted metadata
.plot(cmap=None, cartopy=True)	Interactive visualization
.savefig(filename, cmap=None)	Save plot to image file
.sel(latitude, longitude)	Subset by coordinates
.to_netcdf(filename)	Export to NetCDF4
.to_geotiff(filename)	Export to GeoTIFF
.to_xarray()	Convert to xarray DataArray
.to_sataid(filename)	Write to SATAID format
.to_array()	Return (lat, lon, data) tuple

SataidArray Properties

Property	Description
.lat	1D latitude array (north → south)
.lon	1D longitude array (west → east)
.data	2D calibrated data array
.units	Data units ('Reflectance' or '°C')
.satellite_name	Satellite name (e.g., 'Himawari-9')
.channel_name	Channel name (e.g., 'IR', 'WV')

Dependencies

Required:

• numpy
• matplotlib
• cartopy

Optional:

• netCDF4 (for .to_netcdf())
• rasterio (for .to_geotiff())
• xarray (for .to_xarray())
• scipy (for interpolation in .sel())

License

MIT License - see LICENSE for details.

Author

Sepriando - [e-mail]

Links

• PyPI
• GitHub