Calculating 2-bands EVI from Sentinel-2

Question

I have been trying to calculate Enhanced Vegetation Index (EVI) using Sentinel-2 Level 1C imagery. I have atmospherically corrected the imagery (so the imagery is in BOA) but I can't seem to derive EVI in ArcGIS.

I have been calculating EVI using Raster Calculator using the following formula (2-band EVI):

(2.5 * ("Band 8" - "Band 4")) / ("Band 8" + (2.4 * "Band 4") + 1)

The range of the values are between 2.4 and -1.8 and the theoretical range is between 1 and -1.

Is there anyway that I can correct this?

Answer 1

Sentinel 2 L1C reflectances are multiplied by 10000. Therefore you should adapt your equation in order to take the into account (or you can divide all values by 10000, but I wouldn't do this). On the other hand, it is worth noting that, while most values will ly between -1 and 1, EVI could mathematically be out of this range.

(2.5 * float("Band 8" - "Band 4")) / ("Band 8" + (2.4 * "Band 4") + 10000)

As a remark, I don't see the reason to use "2 bands" EVI when you have a multispectral sensor with NIR, red and blue bands available at the highest spatial resolution (in this case of S2, 10 m). According to Huete et al 1997, the original EVI is 2.5 * ((NIR − R)/(1 + NIR + 6R − 7.5B)). The B(lue) band correspond to band 2 of Sentinel-2 MSI, NIR to Band 8 and R(ed) to band 4. As far as I know, no empirical study tried to adjust these parameters for the specific spectral response of the Sentinel-2 MSI bands, but they re "useable" like this.

Answer 2

Late to reply but I have blog post regarding this question and have described in details about EVI calculation in GEE. https://kaflekrishna.com.np/blog-detail/enhanced-vegetation-index-evi-sentinel-2-image-google-earth-engine/

In short, I have used function to compute EVI as:

def getEVI(image):
# Compute the EVI using an expression.
EVI = image.expression(
    '2.5 * ((NIR - RED) / (NIR + 6 * RED - 7.5 * BLUE + 1))', {
        'NIR': image.select('B8').divide(10000),
        'RED': image.select('B4').divide(10000),
        'BLUE': image.select('B2').divide(10000)
    }).rename("EVI")

image = image.addBands(EVI)

return(image)