Sure you can

But first you have to convert the radiance value of the Landsat 8 to reflectance value by doing Top of atmosphere correction otherwise you will get values larger than 1 and meaningless values.

If you need more information about how to do the TOA correction I can send you details about it.

The enhanced vegetation index (EVI) is an 'optimized' index designed to enhance the vegetation signal with improved sensitivity in high biomass regions and improved vegetation monitoring through a de-coupling of the canopy background signal and a reduction in atmosphere influences. EVI is computed following this equation

use the following formula for EVI = G *(Band5 - Band4)/(Band5 +C1*Band4 - C2*Band2 +L) 

Where band4 is the Red color Band2 is the blue color and Band5 is the Near Infra red color.The coefficients adopted in the MODIS-EVI algorithm are; L=1, C1 = 6, C2 = 7.5, and G (gain factor) = 2.5.

Thank you for your answer! and yes, I can convert the radiance value to TOA reflectance. However, so far I know, the original EVI equation was developed for the MODIS data, therefore, can you please provide me any reference for EVI using Landsat data?

Dear Mr. Emran,

I read several research papers one of them is an interesting paper that uses the same EVI (given above) on a Landsat 7 TM and Modis images and they show high resemblance because both were TOA corrected. But they showed differences in NDVI especially in the steep topographic areas.

See the following paper :

Steven Edward Sesnie , Brett Gary Dickson , Steven Sheldon Rosenstock & Jill

Marie Rundall, 2012, A comparison of Landsat TM and MODIS

vegetation indices for estimating forage phenology

in desert bighorn sheep (Ovis canadensis nelsoni)

habitat in the Sonoran Desert, USA, International Journal of Remote Sensing, 33:1, 276-286, DOI:10.1080/01431161.2011.592865

Good luck

you can use these calibration coefficients provided by NASA. I hope this helps.

Well

Thank you all 

Allow me to chip in my contribution according to my experience so far. I have been processing indices from Rapideye images since Monday. There are no challenges when using the ratio VIs. The challenge comes when using the linearized VIs.

I attempted to calculate the EVI using three approaches:

1. Using the EVI formula plus the image DN values - This has been giving very large values

2. Using the EVI formula plus the TOA reflectances - This has also been giving large values

3. Readjusting the constant parameters in the EVI formula (particularly the L parameter). This is after I came across a publication that had used a value of 10000 for the value L (Elshorbagy, A. M. A. (2013). A low-cost rice mapping remote sensing based algorithm. Retrieved from http://dar.aucegypt.edu/handle/10526/3576). There is however no scientific backing as to the use of the value 10000

After reading publications by Huete (1988, 1990 and 2002) it is clear that using the DN values for EVI calculation is the most robust. The TOA calculations overlook the influence of the atmosphere whereas the EVI formula contains constants C1 and C2 to correct to the atmosphere.

I stand to be corrected though. I am still in the process of doing a bit of reading on the same

Thank you Dr Mohamed Awad, 

I shouldn't calculate Index of DN (multi band transformation such as NDVI and NDWI) without Atmospheric correction? 

How i can apply TOA or other atmospheric correction method? 

The above EVI equation is applicable for Landsat OLI sensor? 

I tried to calculate EVI following USGS product guide where they provided EVI equation in this regard. i converted band 2, 4 and 5 to TRUE TOA reflectance, i tried to calculate NDVI first and i get correct values but when i tried with EVI the result values had no meaning, here below i attached what i got. Please i need a clear guide on how EVI should be calculated. https://landsat.usgs.gov/sites/default/files/documents/si_product_guide.pdf

Yes, you can, for more information on spectral index equations you can use the following link: https://geogeek.xyz/list-of-spectral-indices-for-sentinel-and-landsat.html

this may hlep you

https://www.usgs.gov/land-resources/nli/landsat/landsat-enhanced-vegetation-index?qt-science_support_page_related_con=0#qt-science_support_page_related_con

You may want to look at:

Preprint A Model of Color Vision for Remote Sensing 1