Red-Edge Inflection Point 1
An index that calculates the red edge inflection point, which is the wavelength of maximum slope in the red edge region. REIP is sensitive to chlorophyll content and vegetation stress.
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
- Chlorophyll content estimation
- Red edge position detection
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
| Surface type | Typical REIP1 |
|---|---|
| Open water, snow | -0.3 to -0.1 |
| Bare soil, urban | -0.1 to 0.2 |
| Sparse or stressed crops | 0.2 to 0.4 |
| Healthy crops, grassland | 0.4 to 0.7 |
| Dense forest, peak season | 0.7 to 0.9 |
General Formula
Sensor-Specific Formulas
Most-used sensors — click to show code below
| Sensor | Provider | Formula | Band Mapping |
|---|---|---|---|
| Wyvern | 700 + 40 * (((Band 13 + Band 22) / 2 - Band 16) / (Band 19 - Band 16)) | red→Band 13, re1→Band 16, re2→Band 19, nir→Band 22 | |
| ESA | 700 + 40 * (((B4 + B7) / 2 - B5) / (B6 - B5)) | red→B4, re1→B5, re2→B6, nir→B7 |
Spectral Band Visualization — Dragonette-1
Code Examples
Adapted for Dragonette-1 bands —
Frequently Asked Questions
What is the REIP1 (Red-Edge Inflection Point 1) and when should I use it?
An index that calculates the red edge inflection point, which is the wavelength of maximum slope in the red edge region. REIP is sensitive to chlorophyll content and vegetation stress. 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. REIP1 is particularly suited for chlorophyll content estimation, red edge position detection, vegetation stress monitoring. The general formula is 700 + 40 * (((red + nir) / 2 - re1) / (re2 - re1)), which requires red and re1 and re2 and nir spectral bands.
Which satellite sensors can I use to calculate REIP1?
REIP1 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 700 + 40 * (((Band 13 + Band 22) / 2 - Band 16) / (Band 19 - Band 16)), while Dragonette-2/3 uses 700 + 40 * (((Band17 + Band26) / 2 - Band20) / (Band23 - Band20)). Select a sensor above to see its specific band mapping.
What spectral bands does REIP1 require and why?
REIP1 requires red (670), re1 (700), re2 (740), nir (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 REIP1 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 REIP1 compare to NDVI and other vegetation indices?
While NDVI is the most common vegetation index, REIP1 provides complementary information that NDVI cannot capture on its own. The choice of index depends on your application, sensor availability, and atmospheric conditions.
REIP1 vs other vegetation indices
| Index | Name | How it differs |
|---|---|---|
| ARI | Anthocyanin Reflectance Index | Alternative vegetation index — different band combination |
| mARI | Modified Anthocyanin Reflectance Index | Refined formulation for specific conditions |
| ARVI | Atmospherically Resistant Vegetation Index | Atmospherically corrected version |
| ARVI2 | Atmospherically Resistant Vegetation Index 2 | Atmospherically corrected version |
Related Vegetation Indices
References
Need help choosing?
Ask our AI assistant for sensor recommendations, code examples, or how REIP1 compares to other indices for your specific use case.