Normalized Difference Vegetation Index (NDVI) & Normalized Difference Water Index (NDWI) are two remote sensing indices used to interpret the vegetation. What different interpretation do they offer about the vegetation? Where are they used in practice? What are the cases when NDVI and NDWI are not correlated?
Dear Nikhil
The NDVI (= f(rNIR,rR)) is more sensitive to chlorophyll content in leaves (so to greean leaves area), while NDWI (=f(rNIR, rSWIR)) is sensitive to water content in leaves (so to water stress).
another version of NDWI (=f(rGREEN, rNIR)) informs about water content in water bodies.
In pratice, NDVI is largely used to monitor vegetaion growth since this index is strongly correlated to leaf area index. see for exemple: Article Monitoring wheat phenology and irrigation in Central Morocco...
)The NDWI (=f(rNIR, rSWIR) is communly used to monitor vegetation water stress and thus can be used in the field of irrigation management for example. (see for example : Article Assessment of vegetation water content in wheat using near a...
)ps:
rNIR, rR, NIR, SWIR, GREEN refer to the reflectances in the domains: Near Infrared, Red, Short-wavelength infrared and Green, respectively.
good luck
R.Hadria
Dear Nikhil
The NDVI (= f(rNIR,rR)) is more sensitive to chlorophyll content in leaves (so to greean leaves area), while NDWI (=f(rNIR, rSWIR)) is sensitive to water content in leaves (so to water stress).
another version of NDWI (=f(rGREEN, rNIR)) informs about water content in water bodies.
In pratice, NDVI is largely used to monitor vegetaion growth since this index is strongly correlated to leaf area index. see for exemple: Article Monitoring wheat phenology and irrigation in Central Morocco...
)The NDWI (=f(rNIR, rSWIR) is communly used to monitor vegetation water stress and thus can be used in the field of irrigation management for example. (see for example : Article Assessment of vegetation water content in wheat using near a...
)ps:
rNIR, rR, NIR, SWIR, GREEN refer to the reflectances in the domains: Near Infrared, Red, Short-wavelength infrared and Green, respectively.
good luck
R.Hadria
R. Hadria Thank you for your to the point answer with evidence! Are NDVI and NDWI not correlated to each other? What are the cases when their correlation is poor?
Dear Nikhil
Both indices are highly linear correlated, especially for herbaceous crops (see for example figure 8 in Article Relation of normalized difference vegetation index with some...
)Such correlation is normal since more the plants are well watered, more the leaves are green (in general). The poor correlation between the two indices can be related to tolerance of plants to water stress: high NDVI and law NDVI.
Please, note that this is a simple possible explanation. See in the literature for further details.
rachid
Dear Nikhil
Both indices are highly linear correlated, especially for herbaceous crops (see for example figure 8 in Article Relation of normalized difference vegetation index with some...
)Such correlation is normal since more the plants are well watered, more the leaves are green (in general). The poor correlation between the two indices can be related to tolerance of plants to water stress: high NDVI and law NDVI.
Please, note that this is a simple possible explanation. See in the literature for further details.
rachid
Dear Nikhil Joshi,
01. Normalized Difference Vegetation Index (NDVI):
Quantifies vegetation by measuring the difference between near-infrared (which vegetation strongly reflects) and red light (which vegetation absorbs).
NDVI always ranges from -1 to +1. But there isn’t a distinct boundary for each type of land cover.
For example, when you have negative values, it’s highly likely that it’s water. On the other hand, if you have a NDVI value close to +1, there’s a high possibility that it’s dense green leaves.
But when NDVI is close to zero, there isn’t green leaves and it could even be an urbanized area.
Normalized Difference Vegetation Index (NDVI) uses the NIR and red channels in its formula.
NDVI = (NIR-Red)/(NIR+Red)
Healthy vegetation (chlorophyll) reflects more near-infrared (NIR) and green light compared to other wavelengths. But it absorbs more red and blue light.
This is why our eyes see vegetation as the color green. If you could see near-infrared, then it would be strong for vegetation too.
02. Normalized Difference Water Index (NDWI):
Vegetation cover on the Earth's surface undergoes severe stress during a drought. If affected areas are not identified in time, entire crops may be damaged. The early detection of water stress can prevent many of the negative impacts on crops. Remote sensing of land and the NDWI index can control irrigation in real time, significantly improving agriculture, especially in areas where meeting the need for water is difficult.
Normalized Difference Water Index (NDWI), introduced for the first time in 1996 in Gao (Gao), reflects moisture content in plants and soil and is determined by analogy with NDVI as:
NDWI= NIR-SWIR/NIR+SWIR
NIR - near infrared range with wavelengths in the range of 0.841 - 0.876 nm SWIR - a part of the range with wavelengths in the range of 1.628-1.652 nm
The functionality of the formula is explained by the following considerations: instead of using the red range, the reflection intensity in which is determined by the presence of chlorophyll, a short-wave near-infrared (SWIR) is used in which high absorption of light by water occurs. A wider range of 1500-1750 nm is possible. The use of the same near infrared (NIR) as in the case of NDVI is due to the fact that water does not absorb this part of the electromagnetic spectrum, thus the index is resistant to atmospheric effects, distinguishing it from NDVI.
Note that when observing forests, the NDWI index is characterized by a more stable decrease in values upon reaching critical anthropogenic load, which can serve as an indicator of the ecological state of forests more sensitive than NDVI.
The results of NDWI can be presented in the form of maps and graphs, providing information on both the spatial distribution of water stress on vegetation and its temporal evolution over longer periods of time.
The NDWI product is dimensionless and varies from -1 to +1, depending on the hardwood content, as well as the type of vegetation and cover. The high NDWI values (in blue) correspond to high plant water content and coating of high plant fraction. Low NDWI values (in red) correspond to low vegetation content and cover with low vegetation. During periods of water stress the NDWI rate will decrease.
The NDWI index for assessing risk of fire is used to determine the presence of moisture in vegetation cover. Higher NDWI values indicate sufficient moisture, while a low value indicates water stress.
Relation between NDVI and NDWI is shown through Research Articles as shown below for your better understanding:
01. Article Evaluation of MODIS NDVI and NDWI for vegetation drought mon...
02. Article Comparative Analysis of Normalised Difference Spectral Indic...
I hope I have answered your question.
With Best Wishes,
Samir G. Pandya
Hi,
In addition to other answers, you may which to consider other vegetation indices besides NDVI. There is a limitation using NDVI. Please, see the attached document
Good question. I have also noticed strong correlations between NDVI and NDWI. As Samir Pandya said, the main difference is that NDVI uses a red band where NDWI uses a SWIR band. Assuming a predominantly leafy canopy, these indices should be correlated as much as leaf water content is correlated with leaf chlorophyll content.
However, I have noticed that NDVI and NDWI are not as strongly correlated if the canopy includes additional non-leaf canopy layers with pigments that confound NDVI. For instance, white or yellow flowers reflect red light and that reduces NDVI values. That is potentially a problem for NDVI because visible light is sensitive to pigments whereas as SWIR is not influenced by pigments, making NDWI a more robust correlate for grain yield, etc.
NDVI — Normalized Difference Vegetation Index
NDVI is calculated from comparison of visible and near-infrared light reflected from vegetation. A green pigment in leaves that is chlorophyll greatly absorbs visible light (from 0.4 to 0.7 microns) for photosynthesis process. At the same time, structure of cells of leaves greatly reflects near-infrared light (from 0.7 to 1.1 microns). Healthy vegetation absorbs a major part of visible light while it also reflects a larger part of near-infrared light. Unhealthy or scarce vegetation reflects visible light mostly and a lesser part of near-infrared light.
NDVI = (NIR — VIS) / (NIR + VIS)
NDWI Normalized Difference Water Index
NDWI in comparison with NDVI is more accurate indicator of plant humidity. NDWI is calculated with the help of water absorption band which is more closely connected with moisture than chlorophyll whose light-absorbing properties are used in calculation of NDVI. During droughts vegetation condition greatly depends on water stress and in this case Normalized Difference Water Index is more useful than chlorophyll-based Normalized Difference Vegetation Index.
NDVI is sensitive generally to plant biomass and nitrogen status, while NDWI is sensitive generally to plant biomass and water status. One interprets vegetative nitrogen stress signatures, while the other water stress.
I believe vegetation index from normalized ratio are widely used in practice, supporting management and simulation modeling, so to know vegetation status within biological systems. However, note that vegetation indices like NDVI are often bandied about; and rather, as expressed on RG and in literature, a clear delineation of spectral phenomena is valuable.
I suggest that NDVI would not correlate with NDWI when plant nitrogen and plant water status diverge significantly.
Good questions, and answers are informative, thank you.
As mentioned above there is correlation between visible and SWIR bands. therefore, the relation between the two mentioned indices.
A suggested situation for poor correlation is for non green vegetation - healthy plants with red leaves - did any one tried it?
In relation to switching red and SWIR bands suggested to look at
Article SWIR-based spectral indices for assessing nitrogen content i...
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