Dear Jennifer,
NDVI (normalized difference vegetation index) is the ratio of the difference to the sum of the vegetation reflectance in red and near-infrared (NIR) wavebands of radiation. Since healthy plants reflect the NIR vigorously and absorbs the red strongly, the estimation of NDVI can inform of vegetation condition, photosynthetic activity and stressed conditions of plants. It also varies widely with species.
The ‘temporal change’ means the change with time. The temporal changes in NDVI can point out a lot of parameters varying with time, such as seasonal changes of deciduous forests, algal bloom, stages of crop cycle and many others. You can see our publication: “Temporal change of canopy reflectance at visible wavelength as a biophysical indicator of jute (Corchorus capsularis L.) growth”, B. RayChaudhuri and S. Bhattacharyya, International Journal of Remote Sensing, vol. 28, pp. 5237–5253, 2007, where temporal change of canopy growth was sensed in terms of visible wavebands.
The ‘spatial change’ means the change with place. The variation of NDVI throughout different zones of a given area can sort out stressed vegetation, identify different species, point out changes in weather condition and serve other distinguishing purpose.
Hi Jennifer,
NDVI (normalized difference vegetation index) is a direct measure of the photosynthetic activity of plants, but aggregates across a wide diversity of vegetation types and structures. Thus when there are changes through time of NDVI, the observation is related to changes in the number of leaves (leaf area index) that are actively using their chlorophyll structures. When you see differences across space, then that can be related to differences in vegetation type (from tundra to forest or from desert to wetter areas) or differences in weather (a region getting normal rainfall, or one getting below average rainfall, resulting in a change in the behavior of plants).
What specifically are you interested in?
Molly
I understand either Jenifer is collecting information or behaving like a teacher by asking question to test the knowledge of the community of this forum. All her queries can be satisfactorily be answered, if instead of asking them in this topic she does a little googleing searching expert literature. Variety of queries posed by stand testimony to this observation. If I am wrong, and she has a purpose behind her queries, I offer my unconditional apologies to her.
@ Molly Brown, i was just making my thesis report, so i wanna know whether i should include that term or not, as I have to determine difference in vegetation, but area is same, since the relevant research papers i studied had used this terminology excessively, anyhow thanks for your kind help....
You can use lots of VI like NDVI, simple VI, enhanced VI for soil differentiation etc. If you are interested in floods or water variation content you can subs-tract valuable information on the effects of flooding either spatial or temporal.
Dear Jennifer,
NDVI (normalized difference vegetation index) is the ratio of the difference to the sum of the vegetation reflectance in red and near-infrared (NIR) wavebands of radiation. Since healthy plants reflect the NIR vigorously and absorbs the red strongly, the estimation of NDVI can inform of vegetation condition, photosynthetic activity and stressed conditions of plants. It also varies widely with species.
The ‘temporal change’ means the change with time. The temporal changes in NDVI can point out a lot of parameters varying with time, such as seasonal changes of deciduous forests, algal bloom, stages of crop cycle and many others. You can see our publication: “Temporal change of canopy reflectance at visible wavelength as a biophysical indicator of jute (Corchorus capsularis L.) growth”, B. RayChaudhuri and S. Bhattacharyya, International Journal of Remote Sensing, vol. 28, pp. 5237–5253, 2007, where temporal change of canopy growth was sensed in terms of visible wavebands.
The ‘spatial change’ means the change with place. The variation of NDVI throughout different zones of a given area can sort out stressed vegetation, identify different species, point out changes in weather condition and serve other distinguishing purpose.
Hi Jennifer,
'Temporal' difference stand for changes/differences (of NDVI or any other thing) through 'time' i.e. if you are comparing 2005 data with 2006, 2007, and so on from the 'same area' then you will call it temporal changes/differences.
'Spatial' difference in NDVI mean difference in value of NDVI taken from 'different areas' in a given time i.e. here area is different and time is same. For eg. if you compare NDVI of England and France taken in May 2011 then you will call it spatial difference.
NDVI is the most simplest and an efficient indicator that reflects the vegetation abundance on the Earth's surface. Unlike other indicators, NDVI has many advantages.
Disadvantages: not efficient in complex canopied ecosystems
Not efficient in water-dominated places
Nevertheless, its the most efficient and widely used
Temporal means time and spatial means space. High temporal resolution data means it is collected frequently, and high spatial resolution means the pixel (picture elements) are smaller in size (e.g,. 1 m compared to 30 m).
NDVI (normalized difference vegetation index) is a direct measure of the photosynthetic activity of plants, but it also differentiate an image to forest and non- forest of class in simple meaning.suppose every satellite image have an vegetation band which reflect forest type very easily so that we can use +IR and -IR formula for extract Forest types from an image. NDSI also work in same manner these model commonly works on Algos and Bands value.
NDVI is an excellent measure of vegetation in early to moderate vegetation density. In very dense or high biomass canopies (peak growing seasons in crops, tropical forests, etc.), NDVI saturates and is no longer sensitive to changes in vegetation structure. This is when it is useful to use a different vegetation metric like simple ratio, or the Chlorophyll Index. Each VI has their strengths and weaknesses.
All indices using red and near IR saturate in the same way. The reason for this is related to the fact that there are only so many photons striking a plant leaf and at a certain point, the chlorophyll absorbs nearly all the red energy to the point where no matter how much vegetation you add, more photons cannot be absorbed because they are already all absorbed. It is normally the red band that saturates. So any index using the red energy will suffer from the same limitation. The Enhanced Vegetation Index (EVI) is not supposed to saturate as badly as the NDVI, but this is because a blue band is included in the index that is used to adjust the index for lower contrast due to atmospheric attenuation so their is less atmospheric affect. The EVI therefore works a bit better in areas of the planet where there is greater atmospheric attenuation due to factors like water vapor, which is why it usually works a bit better in the equatorial regions of the earth, but my students and I compared NDVI to EVI for thousands of locations around the US and at various times of the year and found the correlation between the AVHRR NDVI and the MODIS EVI was very strong (r-square of 0.99). Other studies I have done show the correlation between most vegetation indices is extremely high, so I would not anticipate greatly improved results by finding a better index. I have found that replacing the red band with the green band in the NDVI equation greatly improves my ability to discriminate among soybean leaves based on the age of the plant. This is because while the red band saturates, there is still variability in the green region of the spectrum that is influenced by chlorophyll concentrations.
Anthony, I noticed you are probably working at CALMIT in Nebraska. The comment above about using the green band vs the red band is well confirmed by work done there at CALMIT by Anatoly Gitelson who does some amazing work. Don Runquist and Jim Merchant and I go back a long ways.
Kevin,
You are right. I work in CALMIT with Anatoly Gitelson. Don Runquist is also on my committee. I know I have heard Anatoly speaking fondly about your work as well. I agree that changing to a green or red edge band alleviates the problem of saturation by the red band (this is why simple ratio is so noisy at high biomass/veg fraction/green leaf area); however, normalized different indices also suffer saturation at high values of biomass due to the mathematical properties of using ND with greatly contrasting reflectance values.
For example, in crops with very high NIR, like soybean, where NIR can reach 55-60%, even with changes in the green band, Green NDVI will become less sensitive at higher NIR signals.
NIR(%) Green(%) Green NDVI % difference
60 15 0.6
60 14 0.6216 3.478
60 13 0.6438 3.450
60 12 0.6667 3.424
60 11 0.6901 3.401
60 10 0.7143 3.380
60 9 0.7391 3.361
60 8 0.7647 3.344
60 7 0.7910 3.330
60 6 0.8182 3.317
60 5 0.8462 3.306
60 4 0.875 3.297
60 3 0.9048 3.289
60 2 0.9355 3.284
As you can see this effect is less obvious compared to the saturation of NDVI due to the insensitivity of the red band; however, this explains the non-linearity of ND Vis and reduced sensitivity at higher values of Chlorophyll-related biophysical proprieties.
I apologize that my table didn't turn out as good as I hoped (very difficult to read here on this forum). I spent quite a bit of time putting the spaces in, but apparently this forum doesn't really support tables. I just did this example in Excel and copy/pasted it here while calculating the percent difference. As you can see, the % decrease goes from 3.478% to 3.284%, indicating that there is some saturation in this index as well. I will also admit that green reflectance rarely goes below 5% in most canopy conditions.
Anthony, thanks for the example. If you can add the NDVI (red) comparison to the NDVI (green) to your table, I think this would make a great example for contrasting the two indices. If you do this, I would really appreciate getting a copy of the Excel spreadsheet in an email ([email protected]). Please tell Don, Jim and Anatoly hi from Kevin when you see them. Good luck in your graduate program and I will probably see your postings and you will see mine from time-to-time.
Kevin,
I will send you a copy of the excel file; however, you can replace 'green' with 'red' and the same effect will occur. The only difference is that Red typically reaches reflectance as low as 2%, while green reflectance doesn't approach that level. My spreadsheet is just an example on how it works. There is a little discussion in Anatoly's paper: http://calmit.unl.edu/people/agitelson2/pdf/JPP-04.pdf
However, most of it is focused on the point you made in your earlier post regarding to the saturation of Red reflectance, but also discusses how NIR reflectance over 30% coincides with the saturation of NDVI.
Once I get your spreadsheet, I will play with it a bit, but send you back an example of spectral measurements of soybean leaves of different ages and how they vary spectrally. The red bad cannot be used to distinguish between the three leaves, but the green band can.
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