Red-Edge Position Linear Interpolation (REP) is a spectral index that detects the red-edge position through linear interpolation. The red-edge position is a key indicator of vegetation health, chlorophyll content, and plant stress, representing the inflection point between red absorption and NIR reflectance.

Used in crop monitoring.

When to use

  • Time-series monitoring of crop health, growth stages, and stress detection
  • Land cover classification and vegetation type discrimination
  • Biomass estimation and net primary productivity studies
  • Drought impact assessment over agricultural and forest areas
  • Phenology tracking — green-up, peak season, and senescence
  • hyperspectral remote sensing - red-edge position
  • vegetation health monitoring

Limitations

  • Saturates in dense canopies (LAI > 3) — values plateau and lose discrimination ability
  • Sensitive to atmospheric scattering, especially blue-band haze
  • Soil background contaminates measurements in sparsely vegetated areas
  • Sun-sensor geometry (BRDF effects) introduces variability across acquisitions
  • Cloud cover and shadows produce invalid pixels that need masking
  • Requires four or more bands — limits portability across simpler sensors

What the values mean

-1 Water / Snow
-0.1 Bare ground / Built-up
0.1 Sparse / Stressed
0.3 Moderate vegetation
0.5 Healthy vegetation
0.7 Dense canopy
Surface typeTypical REP
Open water, snow-0.3 to -0.1
Bare soil, urban-0.1 to 0.2
Sparse or stressed crops0.2 to 0.4
Healthy crops, grassland0.4 to 0.7
Dense forest, peak season0.7 to 0.9

General Formula

670 670
700 700
740 740
780 780

Sensor-Specific Formulas

Most-used sensors — click to show code below

SensorProviderFormulaBand Mapping
WyvernBand 16 + 40 * ((Band 13 + Band 22)/2 - Band 16) / (Band 19 - Band 16)670→Band 13, 700→Band 16, 740→Band 19, 780→Band 22
ESAB5 + 40 * ((B4 + B7)/2 - B5) / (B6 - B5)670→B4, 700→B5, 740→B6, 780→B7

Spectral Band Visualization — Dragonette-1

Code Examples

Adapted for Dragonette-1 bands —

rep_dragonette-001.py

Frequently Asked Questions

What is the REP (Red-Edge Position Linear Interpolation) and when should I use it?

Red-Edge Position Linear Interpolation (REP) is a spectral index that detects the red-edge position through linear interpolation. The red-edge position is a key indicator of vegetation health, chlorophyll content, and plant stress, representing the inflection point between red absorption and NIR reflectance. Vegetation indices quantify plant health, biomass, and photosynthetic activity by exploiting the contrast between how plants absorb visible light for photosynthesis and reflect near-infrared radiation from their cellular structure. REP is particularly suited for hyperspectral remote sensing - red-edge position, vegetation health monitoring, chlorophyll content estimation. The general formula is 700 + 40 * ((670nm + 780nm)/2 - 700nm) / (740nm - 700nm), which requires 670 and 700 and 740 and 780 spectral bands.

Which satellite sensors can I use to calculate REP?

REP is supported by 3 satellite sensors in our database, including Dragonette-1, Dragonette-2/3, Sentinel-2. Each sensor uses different band designations — for example, Dragonette-1 uses the formula Band 16 + 40 * ((Band 13 + Band 22)/2 - Band 16) / (Band 19 - Band 16), while Dragonette-2/3 uses Band20 + 40 * ((Band17 + Band26)/2 - Band20) / (Band23 - Band20). Select a sensor above to see its specific band mapping.

What spectral bands does REP require and why?

REP requires 670 (670), 700 (700), 740 (740), 780 (780). Vegetation strongly absorbs red light for photosynthesis while reflecting near-infrared light from its mesophyll cell structure, making this contrast a reliable indicator of plant vigour.

How do I calculate REP in Python or R?

Both Python and R code samples are provided above. In Python, use rasterio to load individual band GeoTIFF files and numpy for the arithmetic. In R, the terra package handles raster operations efficiently. The key is to load bands as floating-point arrays to avoid integer division, and to handle division-by-zero cases where the denominator equals zero. For production use, consider applying a valid data mask to exclude no-data pixels before calculation.

How does REP compare to NDVI and other vegetation indices?

While NDVI is the most common vegetation index, REP provides complementary information that NDVI cannot capture on its own. The choice of index depends on your application, sensor availability, and atmospheric conditions.

REP vs other vegetation indices

IndexNameHow it differs
ARIAnthocyanin Reflectance IndexAlternative vegetation index — different band combination
mARIModified Anthocyanin Reflectance IndexRefined formulation for specific conditions
ARVIAtmospherically Resistant Vegetation IndexAtmospherically corrected version
ARVI2Atmospherically Resistant Vegetation Index 2Atmospherically corrected version

Related Vegetation Indices

References

Terrestrial chlorophyll index studies (1988-2011)
Spectral resolution determination research
Vegetation reflectance and soil contamination analysis

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