# Functions for 10 Vegetation Indices in Python, Matlab and R Languages

The functions provide the mathematical formulas for 10 common vegetation indices, implemented in Python, Matlab and R languages for data analysis and processing in remote sensing applications.

Here are the functions for the 10 vegetation indices in Python, Matlab, and Python:

# Python

## 1. Normalized Difference Vegetation Index (NDVI):

`def ndvi(nir, red):    return (nir - red) / (nir + red)`

## 2. Enhanced Vegetation Index (EVI):

`def evi(nir, red, blue):    return 2.5 * (nir - red) / (nir + 6 * red - 7.5 * blue + 1)`

## 3. Soil Adjusted Vegetation Index (SAVI):

`def savi(nir, red, L=0.5):    return (nir - red) / (nir + red + L) * (1 + L)`

## 4. Transformed Vegetation Index (TVI):

`def tvi(nir, red, green):    return 0.5 * (120 * (nir - green) - 200 * (red - green))`

## 5. Green Normalized Difference Vegetation Index (GNDVI):

`def gndvi(nir, green):    return (nir - green) / (nir + green)`

## 6. Modified Soil-Adjusted Vegetation Index (MSAVI):

`def msavi(nir, red):    return 0.5 * (2 * nir + 1 - np.sqrt((2 * nir + 1) ** 2 - 8 * (nir - red)))`

## 7. Normalized Difference Infrared Index (NDII):

`def ndii(nir, swir):    return (nir - swir) / (nir + swir)`

## 8. Chlorophyll Vegetation Index (CVI):

`def cvi(nir, red):    return nir / red - 1`