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How to generate a vegetation index - PIX4Dfields

The following article describes how to generate vegetation indices using the default index options and how to generate a customized index using the index calculator.
The complete workflow on how to import and process drone images to generate a vegetation index is described in My first vegetation index map - 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 orthomosaic after processing the images.

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

Test4.gif

Note: The most commonly used vegetation indices are available by default in PIX4Dfields. However, the spectral composition of your dataset will determine which vegetation indices are available to generate. For example, the list of default indices will be different for RGB versus multispectral imagery due to the different composition of spectral bands.

Available indices

Note: Try PIX4Dfields now! Register for a free 15 days trial, and download our Example datasets to learn how easy it is to generate all these indices.
Index
Description
Formula
Image import type
Platform
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)
Drone and satellite.
GNDVI - Green Normalized Difference Vegetation Index
NDVI index without red channel availability, for areas sensitive to chlorophyll content.
(nir - green) / (nir + green)
Multispectral
Drone and satellite.
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
Drone and satellite.
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
Drone and satellite.
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
Drone and satellite.
NDVI - Normalized Difference Vegetation Index
Generic index used for leaf coverage and plant health.
(nir - red) / (nir + red)
Multispectral
Drone and satellite.
SIPI2 - Structure Intensive Pigment Index 2

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

(nir - green) / (nir - red)
Multispectral
Drone and satellite.
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
Drone and satellite.
VARI - Visible Atmospherically Resistant Index
RGB index for leaf coverage.
min(1; max(-1; (green - red) / (green + red - blue) ))
RGB
Drone and satellite.
NDMI - Normalized Difference Moisture Index
NDWI uses the NIR and SWIR bands to monitor changes in water content of leaves.
(nir - swir_1613) / ( nir + swir_1613)
Multispectral
Satellite
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 Available 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 now appears 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 Available bands.

Note: Single-band reflectance maps can be generated using the index calculator. For more information: How to generate reflectance maps with PIX4Dfields?

The Operations buttons are described below:

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

Understanding the NDVI

The NDVI (Normalized Difference Vegetation Index), the so-called "Green Index", is sensitive to chlorophyll content.

Healthy vegetation absorbs most of the visible light that hits it and reflects a large portion of the near-infrared light. As a result, healthy vegetation will have a high NDVI value.

The NDVI scale ranges from -1 to +1. This scale is designed to represent different types of land cover and vegetation health or density. Here's a brief overview of what values within this range typically indicate:

  • Values close to +1: High NDVI values (close to +1) indicate dense green leaves and are typically associated with healthy, vigorous vegetation. This is because healthy vegetation reflects more near-infrared (NIR) light and absorbs more visible light.
  • Values close to 0: NDVI values around 0 indicate barren areas of rock, sand, or snow, where there is little difference in the reflectance between the red and NIR wavelengths, suggesting minimal vegetation.
  • Values close to -1: Negative NDVI values (close to -1) are possible but less common and can occur when the reflectance in the red wavelength is greater than the reflectance in the NIR wavelength. This situation might be observed in water bodies, where the absorption of NIR is higher than the absorption of visible light, resulting in negative NDVI values.

It's important to note that NDVI values are influenced by the specific characteristics of the area being observed, including the type of vegetation, the stage of growth, and the presence of any stress factors (like water availability or diseases). Here's a more detailed breakdown of the NDVI value obtained for a wheat field data provided in My first vegetation index map - PIX4Dfields:

  • -1.0 to 0.0: There are no pixels with these values, as it's mainly related to non-vegetated surfaces, (water, snow, clouds, etc.)
  • 0.0 to 0.5: Bare soil, as evident from the machine tire marks.
  • 0.5 to 0.7: Non-healthy vegetation, low plant density.
  • 0.5 to 0.7: Healthier vegetation.
  • 0.9 to 0.973: Dense vegetation, healthy crops at peak vitality.