By Shubham Jayanand Berad (Shivaji University Student)
Understanding Vegetation Indices: NDGI, Clgreen, and Clred-edge
Remote sensing technologies have revolutionized the way we monitor vegetation health, growth, and biomass across landscapes. Among the tools utilized are vegetation indices, mathematical formulas that process reflectance data captured by multispectral or hyperspectral sensors. This article focuses on three widely used indices: NDGI (Normalized Difference Greenness Index), CIgreen (Green Chlorophyll Index), and CIred-edge (Red-Edge Chlorophyll Index).
1. NDGI (Normalized Difference Greenness Index)
Overview:
The NDGI is a spectral index used to quantify greenness, primarily associated with the presence of chlorophyll in vegetation. It is similar in concept to the NDVI (Normalized Difference Vegetation Index), but it uses the green band instead of the near-infrared band.
Formula:
NDGI = NDGI=(Green−Red)(Green+Red)NDGI = frac{(Green – Red)}{(Green + Red)}
Bands Used:
- Green band (typically 0.54–0.58 μm)
- Red band (typically 0.64–0.67 μm)
Applications:
- Estimating vegetation health and vigor
- Detecting crop stress and disease
- Assessing greenness in urban or mixed land-cover environments
- Monitoring seasonal changes in vegetation
Interpretation:
- High NDGI values indicate dense and healthy green vegetation
- Low or negative values can suggest bare soil, senescent vegetation, or built-up areas
2. CIgreen (Green Chlorophyll Index)
Overview:
CIgreen is a chlorophyll-sensitive vegetation index designed to estimate chlorophyll content in plants, especially useful in crop monitoring. It is particularly valuable for applications in precision agriculture.
Formula:
CIgreen=NIRGreen−1CI_{green} = frac{NIR}{Green} – 1CIgreen=GreenNIR−1
Bands Used:
- NIR (Near-Infrared) band (typically 0.76–0.90 μm)
- Green band (typically 0.54–0.58 μm)
Applications:
- Quantitative estimation of leaf chlorophyll content
- Monitoring nitrogen levels in crops
- Assessing crop maturity and biomass accumulation
- Detecting early plant stress
Interpretation:
- Higher CIgreen values indicate higher chlorophyll content, usually signifying healthy, photosynthetically active vegetation.
- Useful for site-specific nutrient management (e.g., variable-rate fertilization)
3. CIred-edge (Red-Edge Chlorophyll Index)
Overview:
CIred-edge is a more advanced chlorophyll index that leverages the red-edge spectral region, which is highly sensitive to changes in chlorophyll concentration. This region lies between the red and NIR bands and is particularly useful for early detection of crop stress before it becomes visible.
Formula:
CIred−edge=NIRRedEdge−1CI_{red-edge} = frac{NIR}{RedEdge} – 1CIred−edge=RedEdgeNIR−1
Bands Used:
- NIR band (typically 0.76–0.90 μm)
- Red-edge band (typically 0.70–0.74 μm)
Applications:
- Precision agriculture and nutrient management
- Early detection of crop stress, disease, or water deficit
- Mapping of vegetation phenology and chlorophyll gradients
- Monitoring forestry and ecological restoration projects
Interpretation:
- Higher CIred-edge values correspond to higher chlorophyll content
- More sensitive than NDVI or CIgreen for detecting subtle or early vegetation changes
Comparison Table
| Index | Key Focus | Formula | Sensitivity | Applications |
| NDGI | Greenness | (Green – Red)/(Green + Red) | General greenness | Urban, crops, basic vegetation |
| CIgreen | Chlorophyll (Green) | (NIR / Green) – 1 | Moderate | Crop monitoring, N management |
| CIred-edge | Chlorophyll (Red-edge) | (NIR / RedEdge) – 1 | High | Early stress detection, precision ag |
Conclusion
Vegetation indices such as NDGI, CIgreen, and CIred-edge serve as essential tools in environmental monitoring, agriculture, and forestry. Each index offers unique insights depending on the spectral bands used and the specific vegetation traits being analyzed. As remote sensing technology continues to advance, integrating multiple indices into decision-making processes allows for more accurate, efficient, and timely management of natural and agricultural ecosystems.
1). DVI (Difference Vegetation Index)
The Difference Vegetation Index (DVI) is a simple vegetation index that quantifies vegetation presence and density by comparing near-infrared (NIR) and red band reflectance. It’s a straightforward way to assess vegetation presence and density, with higher DVI values indicating more vegetation.
Formula:-
DVI = NIR BAND – RED BAND
It’s Works:-
- Calculating the Difference:-
The DVI formula directly calculates the difference between these two reflectance values.
- Interpreting the Results:-
A higher DVI value suggests a larger difference between NIR reflectance and red reflectance, indicating denser or more healthy vegetation. Conversely, lower DVI values suggest sparse or stressed vegetation.
- Simplicity and Sensitivity:-
DVI is a simple index, making it computationally easy to calculate, but it can be sensitive to variations in soil and atmospheric conditions, according to a paper in IOP Science.
- Comparison to NDVI:-
While DVI is a basic index, it’s less normalized than other indices like the Normalized Difference Vegetation Index (NDVI), which can be more robust to changes in soil and atmospheric conditions, as explained in a paper in IOP Science.
2). MSR (Modified Simple Ratio):-
MSR is a vegetation index used to measure how healthy and green plants are using satellite or drone images. It is an improved version of the Simple Ratio (SR), to vegetation biophysical parameters. It is calculated by taking the ratio of the difference between two spectral bands to their sum.
Formula:
MSR=(NIR/Red)+1(NIR/Red)−1
It’s work:-
- Reflectance Ratios:-
MSR relies on measuring the reflectance of light at different wavelengths from the vegetation canopy. Plants absorb light in the red portion of the spectrum (visible light) and reflect more in the NIR region 9near infrared).
- Simple ratio (SR) Foundation:-
The Simple Ratio (SR) is a basic vegetation index where the reflectance in the NIR is didided by the reflectance in the red band.
- Remote Sensing Applications:-
MSR is commonly used in remote sensing applications, where data from satellite or airborne sensors is used to map vegetation and track its health over time.
- Improved Sensitivity:-
MSR is designed to be more sensitive to changes in vegetation than some other indices, particularly when used in conjunction with other indices like NDVI or RDVI.
3). EV12 (Two-band Enhanced Vegetation Index):-
The two-band Enhanced Vegetation Index (EV12) is a remote sensing technique that estimates vegetation health and biomass using only two spectral bands (NIR and Red). It’s a simplified version of the full EVI, designed for use when a blue band is unavailable, according to a paper on ResearchGate.
Formula:-
EVI2=2.5×(NIR+2.4×RED+1)(NIR−RED)
It’s Work:-
- Band Selection:
EV12 uses reflectance values from the near-infrared (NIR) and red bands.
- Difference Calculation:-
The Difference between the NIR and red reflectance is calculated.
- Normalization:-
The Difference is then divided by the sum of NIR reflectance, 2.4 times the red reflectance, and 1.
- Interpretation:-
Higher EV12 values indicate healthier and more robust vegetation, reflecting greater chlorophyll content and biomass.
Research Contributors:
- Shubham Jayanand Berad
- (Shivaji University Student)
