How to generate a vegetation index with Pix4Dfields


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Information: The following article describes how to generate vegetation indices using the available indices of Pix4Dfields and generate a customize index using the index calculator.Test4.gif
Note: Below Available indices, there is a list of the most commonly used vegetation indices available by default in Pix4Dfields. The list of indices is different for RGB and multispectral images.
Note: The indices available in Pix4Dfields and that you can generate within the software depend on the bands available on your camera. For example, a RedEdge MX camera has the following bands: Blue, green, red, red edge, near- IR. Therefore, using Pix4Dfields is possible to generate vegetation indices that use the blue, green, red, red edge, or near- IR bands. It is also possible to generate reflectance maps using the index calculator. For more information: How to generate reflectance maps with Pix4Dfields?
Tip: To do soil and plant masking maps using Pix4Dfields see the workaround in our community.

Index generator

To generate predefined indices based on the imported images.

1. Click Index above the Layers Menu. The INDEX GENERATOR tool opens.
2. Select the Source layer first.
3. Select the vegetation index that you want to generate by checking the corresponding boxes.
4. Click GENERATE.

Available indices

Index Description Formula Image import type
BNDVI - Blue Normalized Difference Vegetation Index NDVI index without red channel availability, for areas sensitive to chlorophyll content. (NIR − BLUE) / (NIR + BLUE) Multispectral (excluding Sequoia)
GNDVI - Green Normalized Difference Vegetation Index NDVI index without red channel availability, for areas sensitive to chlorophyll content. (NIR − GREEN) / (NIR + GREEN) Multispectral
LCI - Leaf Chlorophyll Index

Index to assess chlorophyll content in areas of complete leaf coverage.

Value range clamp between -1 and 1.

(NIR − REDEDGE) / (NIR + RED)  Multispectral
MCARI - Modified Chlorophyll Absorption in Reflective Index Index used to measure chlorophyll concentrations including variations in the Leaf Area Index. 1.2 * (2.5 * (NIR - RED) - 1.3 * (NIR - GREEN)) / (normalized to the maximum value of RED, GREEN, and NIR bands) Multispectral
NDRE - Normalized Difference Red Edge Index sensitive to chlorophyll content in leaves against soil background effects. This index can only be formulated when the red edge band is available. (NIR − REDEDGE) / (NIR + REDEDGE) Multispectral
NDVI - Normalized Difference Vegetation Index Generic index used for leaf coverage and plant health. (NIR − RED) / (NIR + RED) Multispectral
SIPI2 - Structure Intensive Pigment Index 2

Index used in areas with high variability in canopy structure (e.g. forestry).

Value range clamp between -1 and 1.

(NIR − GREEN) / (NIR − RED) Multispectral
TGI - Triangular Greenness Index RGB index for chlorophyll sensitivity. (GREEN − (0.39 * RED) − (0.61 * BLUE)) /(normalized to the maximum value of RED, GREEN, and BLUE bands) RGB
VARI - Visible Atmospherically Resistant Index RGB index for leaf coverage. min(1; max(-1; (GREEN − RED) / (GREEN + RED − BLUE) )) RGB, MicaSense
Note 1: min(1, max(-1, ...) is clamping the values between -1 and 1.


Index calculator

To generate a custom index using the index calculator.

1. Open the INDEX GENERATOR by clicking the icon at the top right of the window.
2. Choose the source layer.
3. Click Create custom index below the list of available indices.
4. Name the index.
5. Enter the formula either by clicking the Operations and the Reflectance Map Bands buttons or by using your keyboard.
When a formula is valid, the PREVIEW button turns green.
6. Click the PREVIEW button to preview your index.
7. When you are satisfied with the preview, click APPLY.
8. The generated custom index appears now in the list of layers and in the map interface.

Custom indices can be created depending on the available bands from your imported images, these are listed as buttons under Reflectance Map Bands.

The Operations buttons are described below:

Operation Description
( open parenthesis
) close parenthesis
* multiplication
+ addition
- subtraction
/ division
; (semicolon) separator for functions that take more than one parameter
^ exponentiation
abs absolute value
exp exponential (e^x)
log natural logarithm
max maximum value between two arguments, the separator is ";" (semicolon)
min minimum value between two arguments, the separator is ";" (semicolon)
sqrt square root
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  • Jorge Solorzano


    I am new to Pix4D and I am wondering if it is possible to import one RGB orthomosaic previously generated in another software such as Agisoft and calculate the TGI Index in Pix4D Mapper?

    I have several orthomosaics that have been previously generated by my colleague in metashape but I would like to calculate the TGI index in Pix4D without re-process all the datasets again since I already have the mosaics.

    I was reading the Vegetation Index Documentation and I see that the equation used for TGI is TGI = (GREEN − (0.39 * RED) − (0.61 * BLUE)) /(normalized to the maximum value of RED, GREEN, and BLUE bands). What does "Normalized to the maximum value of R,G,B bands" Mean exaclty? Do you have an example of the equation normalizing with real numbers? so I can understand better the normalization part?

    Kind Regards,




  • Avatar
    Momtanu (Pix4D)

    Jorge, You can use Pix4dFields. You can import the RGB orthomosaic and calculate indices. However, before purchasing, we will recommend to use a trail and testing. The denominator is the max value of red, green and blue bands. You are normalizing the TGI by dividing the index with the max value.



    We have a phantom4pro to collect data.

    Which indexes are the best for showing : hydratation of cultures, rate of chorophylle, density of leafs?

    Is the camera of the p4p suitable for these outputs please.

    Best regards

  • Avatar
    Momtanu (Pix4D)


    The index maps generated will only tell you which areas are stressed/unhealthy. However, you would need to scouting/ground truth validation to understand the reason for the stress. Generally, research says that plant density is directly proportional to vegetation index values from multispectral cameras. 

    Phantom 4 Pro has a RGB camera, thus you will be only able to the visual changes. Multispectral cameras have NIR/Rededge band which is beyond visual spectrum (RGB) and thus helps in the detection. You could use your phantom 4 Pro and do some tests.

    This will help:,


  • Fitsum Tilahun Teshome

    Hi pix4D users, 

    Recently I tried to process a thermal image using "ThermoMAP camera" processing option in pix4d. However, constantly getting "generate index failed" error. what can I do to solve this problem. or which processing option is best to process Zenmuse XT2 camera thermal image? 

    Thank you.

  • Avatar
    Momtanu (Pix4D)

    Can you send us your p4d file and logfile? I would recommend unchecking/disabling the indices generation in processing options and then after step 3 is completed, click on index calculator. Do you still get the error?

  • Abdullah Alawadhi


    I was wondering would it be possible to calculate soil moisture index using pix4d? 

    I have both the parrot anafi thermal and parrot bluegrass multispectral UAVs.


  • Fernanda Bosmediano

    Hello Abdullah, 

    Hope you are doing great. Okay from your cameras I see you have the following bands available: 

    • Bluegrass: Green, RedEdge, Red, Near Infrared, and the RGB camera.  
    • Anafi: LWIR

    Our suggestion is to try many vegetation indices and choose the ones you think best reflects your crops’ health. This is because it is true that each index has a purpose. However, this varies depending on the crop, soil quality, environmental conditions, etc. 

    Once you generate the indices which can be generated with the bands available in your cameras (described above). I will recommend doing ground scouting on those stress areas. You will recognize the reason for the stress: nitrogen deficiency, soil moisture, etc.

    I would recommend starting with the NDVI index. 

    Let us know if this helps



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