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NDVI - Vegetation Health
NDVI - Vegetation Health
NDVI - Vegetation Health
NDVI - Vegetation Health
NDVI - Vegetation Health
Land Usev04.00 credits/per_km2
Responsible:Niccolò Calandri
Layer NDVI - Vegetation Health on real sites
Real Estate UK
Catania
Berlino Quarter
Mina el Cerrejon
NDVI — Normalized Difference Vegetation Index
Overview
The NDVI (Normalized Difference Vegetation Index) is the most widely used spectral index for vegetation monitoring worldwide. It was introduced in 1973 by Rouse et al. at Texas A&M University as part of the ERTS-1 programme (Rouse, J.W. et al., 1974. "Monitoring vegetation systems in the Great Plains with ERTS", Third Earth Resources Technology Satellite-1 Symposium, NASA SP-351, pp. 309–317). The index exploits the contrast between near-infrared reflectance (NIR), which is strongly reflected by chlorophyll, and red reflectance (RED), which is strongly absorbed, to quantify the density and health of vegetation cover.
Values range from -1 to +1:
- Negative values → non-vegetated surfaces (water, snow, clouds)
- Values near 0 → bare soil, rock, desert areas
- Values 0.2 – 0.5 → sparse or stressed vegetation
- Values > 0.6 → dense and healthy vegetation
Calculation Methodology
Formula:
NDVI = (NIR − RED) / (NIR + RED)
Implementation with Sentinel-2 (spatial resolution 10 m):
- NIR = Band 8 (842 nm)
- RED = Band 4 (665 nm)
Preprocessing pipeline:
- Cloud masking — pixels classified via Scene Classification Layer (SCL) as cloud shadow (3), cloud medium (8), cloud high (9), thin cirrus (10), defective (0), dark (1), saturated (2) are excluded
- Water masking — SCL class 6 pixels excluded from computation
- Temporal compositing — median composite over the requested time interval to reduce atmospheric noise
Analysis modes:
| Mode | Description |
|---|---|
normal | Mean NDVI value over the selected period |
range | Difference between seasonal maximum and minimum (phenological amplitude) |
delta | Difference in mean NDVI between two time periods |
Data Sources
| Code | Name | Provider | Type | Coverage | Resolution | Availability |
|---|---|---|---|---|---|---|
WRD_S2XXX_99 | ESA Sentinel-2 L2A | ESA/Copernicus | Multispectral raster | Global | 10 m | 2017-03-28 — present |
Documentation: Copernicus Sentinel-2 SR Harmonized
Quality Range and Levels
| Indicator | Unit | Range | Inverted |
|---|---|---|---|
ndvi | dimensionless | [-1, 0.1, 0.2, 0.5, 0.8, 1] | No |
Inverted = No: a higher value indicates a better condition.
| Level | Thresholds | Ecological Interpretation |
|---|---|---|
| E (Critical) | < 0.1 | No vegetation: water, bare soil, artificial surfaces or snow |
| D (Low) | 0.1 – 0.2 | Very sparse or severely stressed vegetation; arid or degraded soils |
| C (Moderate) | 0.2 – 0.5 | Sparse or moderately stressed vegetation; grasslands, early-stage crops |
| B (Good) | 0.5 – 0.8 | Dense and active vegetation; temperate forests, thriving croplands |
| A (Excellent) | > 0.8 | Very dense and fully healthy vegetation; tropical forests, closed canopy |
Technical Notes
- NDVI maps must be generated from Sentinel-2 imagery
- NDVI is sensitive to residual atmospheric effects, solar angle, and soil brightness; temporal median compositing partially mitigates these factors
- In areas with very dense vegetation, NDVI tends to saturate (poor discrimination above 0.8–0.9); alternative indices such as EVI may be more informative in these contexts
References
- Rouse, J.W., Haas, R.H., Schell, J.A., Deering, D.W. (1974). "Monitoring vegetation systems in the Great Plains with ERTS". Third ERTS-1 Symposium, NASA SP-351, Vol. 1, pp. 309–317.
- Tucker, C.J. (1979). "Red and Photographic Infrared Linear Combinations for Monitoring Vegetation". Remote Sensing of Environment, 8(2), pp. 127–150.
- Huang, S., Tang, L., Hupy, J.P., Wang, Y., Shao, G. (2021). "A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing". Journal of Forestry Research, 32, pp. 1–6.
Quality Ranges and Levels
ndvi
ECritical
DLow
CModerate
BGood
AExcellent
-1 → 0.09
0.1 → 0.19
0.2 → 0.49
0.5 → 0.79
0.8 → 1
E
Critical-1 – 0.09D
Low0.1 – 0.19C
Moderate0.2 – 0.49B
Good0.5 – 0.79A
Excellent0.8 – 1Data Sources & References
Sources
WRD_S2XXX_99
Methodology
NDVI measures vegetation health using the formula:
NDVI = (NIR − RED) / (NIR + RED)
where NIR = Band 8 (842 nm) and RED = Band 4 (665 nm) from Sentinel-2 (10 m resolution).
Preprocessing:
- Cloud masking via SCL (classes 0, 1, 2, 3, 8, 9, 10)
- Water masking (class 6)
- Temporal median composite
Modes: normal (mean), range (min-max), delta (difference between periods).