Working with Sensor Bundles

This chapter documents supported sensor bundle families and common workflows.

Bundle APIs provide a common operational interface across heterogeneous sensor families. The conceptual goal is to standardize ingestion and inspection steps even when archive layout, naming conventions, or QA assets differ between providers.

Supported Families

• Generic auto-detect: wbw_read_bundle(...)
• Landsat: wbw_read_landsat(...)
• Sentinel-1 SAFE: wbw_read_sentinel1(...)
• Sentinel-2 SAFE: wbw_read_sentinel2(...)
• PlanetScope: wbw_read_planetscope(...)
• ICEYE: wbw_read_iceye(...)
• DIMAP: wbw_read_dimap(...)
• Maxar/WorldView: wbw_read_maxar_worldview(...)
• RADARSAT-2: wbw_read_radarsat2(...)
• RCM: wbw_read_rcm(...)

Common Inspection Pattern

Start here to establish what each bundle contains before choosing analysis channels.

library(whiteboxworkflows)

b <- wbw_read_bundle('BUNDLE_ROOT')
print(b$family)
print(b$key_summary())
print(b$list_band_keys())
print(b$list_measurement_keys())
print(b$list_qa_keys())
print(b$list_asset_keys())

Family-Specific Examples

These examples follow one shared shape across providers: load, inspect, sample key channels, then generate QA-ready outputs.

Sentinel-2

Use this for optical band workflows where band identity is explicit.

s2 <- wbw_read_sentinel2('S2_SCENE.SAFE')
red <- s2$read_band('B04')
nir <- s2$read_band('B08')
rgb <- s2$write_true_colour('s2_true_colour.tif')

Landsat

Use this when metadata such as cloud cover and processing level drive filtering.

ls <- wbw_read_landsat('LC09_SCENE')
print(ls$processing_level())
print(ls$cloud_cover_percent())
preview <- ls$read_band(ls$list_band_keys()[[1]])

Sentinel-1 / SAR Families

Use this pattern for SAR measurement access and quick false-colour QA.

s1 <- wbw_read_sentinel1('S1_SCENE.SAFE')
print(s1$polarizations())
meas <- s1$read_measurement(s1$list_measurement_keys()[[1]])
fc <- s1$write_false_colour('s1_false_colour.tif')

PlanetScope / ICEYE / DIMAP / Maxar-WorldView / RADARSAT-2 / RCM

Use this loop for multi-provider intake checks with a consistent script shape.

loaders <- list(
  wbw_read_planetscope,
  wbw_read_iceye,
  wbw_read_dimap,
  wbw_read_maxar_worldview,
  wbw_read_radarsat2,
  wbw_read_rcm
)

paths <- list('PLANETSCOPE_SCENE', 'ICEYE_SCENE', 'DIMAP_SCENE', 'MAXAR_SCENE', 'RADARSAT2_SCENE', 'RCM_SCENE')

for (i in seq_along(loaders)) {
  b <- loaders[[i]](paths[[i]])
  print(c(b$family, b$bundle_root))
}

Recommended Workflow

1. Open with family-specific reader when known.
2. Inspect key groups with key_summary() and list_*_keys().
3. Read representative channels via read_any() or family-specific methods.
4. Generate preview/composite rasters for QA.
5. Persist derived outputs and record source family + key choices.

Calibration Contract Notes (Landsat/Sentinel-2)

Remote-sensing radiometric and thermal tools in WbW-R now rely on a standardized sensor-bundle calibration contract in wbraster.

• Sentinel-2 bundle metadata provides quantification values used for DN to TOA reflectance scaling.
• Landsat bundles provide typed per-band reflectance and thermal constants used in TOA reflectance and LST workflows.

For best results, keep original SAFE/MTL metadata with scene rasters when moving or staging bundle data for analysis.

Sensor Bundle Object Method Reference

Metadata and Key Discovery

Raster Access by Key

Composite Generation

Common Metadata Accessors