Multi-sensor fusion: GOES-East, GOES-West, Himawari-9

One geostationary satellite sees one hemisphere. Three together — GOES-East at 75.2°W, GOES-West at 137.2°W, and JMA Himawari-9 at 140.7°E — give you nearly the entire disk of Earth, with overlap regions for cross-calibration. Fusing them is the foundation of LaunchDetect's global coverage: a plume from any spaceport on Earth, from Mahia (New Zealand) to Kourou (French Guiana), is in at least one satellite's field of view.

Why three satellites

Each geostationary satellite has a useful viewing range of roughly ±70° in longitude and ±70° in latitude from its sub-satellite point. Beyond that, limb effects make data marginal. Combining the three covers from ~10°W (eastern edge of GOES-East) all the way around to ~140°W (western edge of GOES-West, overlapping with Himawari-9's eastern edge at ~70°W effective). The only major coverage gap is the Indian Ocean / Africa-East / Middle East region, covered by Meteosat (which has different bands and is harder to integrate).

The radiometric problem

The three satellites' Band 7 channels are nominally identical (3.9 µm) but in practice differ:

• Different spectral response functions (the exact wavelength sensitivity curve).
• Different ground sampling distances (2 km for ABI, 2 km for Himawari AHI).
• Different vicarious calibration cycles.

The result: a brightness temperature of 320 K from GOES-18 may correspond to 322 K from Himawari-9 looking at the same physical hotspot at the same moment. For absolute comparisons (is this >320 K?) you need cross-calibration. NOAA + JMA publish cross-calibration coefficients quarterly; the alternative is empirical regression against ground truth (SST buoys, etc.).

The time problem

Each satellite scans on its own schedule. GOES Full Disk takes 10 minutes per scan. Himawari Full Disk takes 10 minutes too, but starts at a different moment. To create a synchronized mosaic at time T, you need to interpolate each sensor's coverage to T — which means knowing the per-pixel scan time, not just the file start time. The NetCDFs publish this; satpy handles the interpolation if you ask it to.

The dateline problem

The line where GOES-West and Himawari-9 overlap is near the antimeridian (180°). Naive operations on lat/lon coordinates split a geometry crossing 180° into two pieces (one near -180°, one near +180°). Use a Pacific-centric projection like Mercator centered at 180° (PROJ string: +proj=merc +lon_0=180) to keep the seam continuous:

from rasterio.warp import calculate_default_transform, reproject, Resampling

src_crs = {'init': 'epsg:4326'}
dst_crs = '+proj=merc +lon_0=180 +datum=WGS84'

# Reproject each sensor's frame to Pacific-centric Mercator
transform, width, height = calculate_default_transform(
    src_crs, dst_crs, src.width, src.height, *src.bounds)

Stitching strategies

Where two sensors overlap (e.g., GOES-West and Himawari-9 overlap from ~150°E to ~150°W), choose one as the "master" or blend them:

• Hard cutover — a single longitude boundary; west of it use Himawari, east of it use GOES-West. Simple, but visible seam.
• Linear blend — in the overlap region, take a weighted average that smoothly transitions. Eliminates the visible seam but smears the radiometric truth.
• Quality-weighted — use whichever sensor has the higher view-angle quality (closer to sub-satellite point) at each pixel. Best fidelity but most complex.

For thermal hotspot detection, hard cutover is usually fine — the threshold logic dominates the seam artifact.

The lab

You'll download time-matched GOES-18 (Band 7) and Himawari-9 (AHI Band 7) Full Disk frames over the Pacific from each agency's AWS Open Data bucket, reproject both to a common Pacific-centric Mercator, stitch across the dateline with a hard cutover at 180°, and output a hemispheric mosaic GeoTIFF showing the entire Pacific hemisphere's thermal field. This is the architecture LaunchDetect uses for global launch coverage.