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| Quick links | Description :: Parameters :: Parameter descriptions :: Details :: Algorithm :: References :: Related |
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| Name | Type | Length | Value range |
|---|---|---|---|
| Input1: Blue image channel (0.4-0.52 um) | Raster port | 0 - 1 | |
| Input2: Green image channel (0.52-0.60 um) | Raster port | 0 - 1 | |
| Input3: Red image channel (0.62-0.71 um) * | Raster port | 1 - 1 | |
| Input4: Red edge image channel (0.697-0.713 um) | Raster port | 0 - 1 | |
| Input5: NIR image channel (0.78-0.89 um) | Raster port | 0 - 1 | |
| Input6: SWIR image channel (1.565-1.655 um) | Raster port | 0 - 1 | |
| Input7: SWIR image channel (2.100-2.280 um) | Raster port | 0 - 1 | |
| Input8: Red edge image channel (0.732-0.748 um) | Raster port | 0 - 1 | |
| Input9: Red edge image channel (0.773-0.793 um) | Raster port | 0 - 1 | |
| Input10: NIR image channel (0.855-0.875 um) | Raster port | 0 - 1 | |
| Output: Generated vegetation indices | Raster port | 0 - 1024 | |
| Index to calculate * | String | 2 - 1 | |
| Output type | String | 0 - 1 | 8U | 16S | 16U | 32R Default: 32R |
| Scaling offset | Float | 0 - 2 | |
| Scaling factor | Float | 0 - 2 |
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Input1: Blue image channel (0.4-0.52 um)
The image channel in the input file that contains the blue band.
This parameter is optional.
Input2: Green image channel (0.52-0.60 um)
The image channel in the input file that contains the green band.
This parameter is optional.
Input3: Red image channel (0.62-0.71 um)
The image channel in the input file that contains the red band.
This parameter is mandatory.
Input4: Red edge image channel (0.697-0.713 um)
The image channel in the input file that contains the RedEdge (0.697-0.713 um) band.
This parameter is optional.
Input5: NIR image channel (0.78-0.89 um)
The image channel in the input file that contains the near-infrared (NIR) band.
This parameter is optional.
Input6: SWIR image channel (1.565-1.655 um)
The image channel in the input file that contains the shortwave-infrared SWIR (1.565-1.655 um) band.
Use this input specifically to calculate the Green Vegetation Index (GVI) on Landsat-7 and Landsat-8 data.
This parameter is optional.
Input7: SWIR image channel (2.100-2.280 um)
The image channel in the input file that contains the shortwave-infrared SWIR (2.100-2.280 um) band.
Use this input specifically to calculate the Green Vegetation Index (GVI) on Landsat-7 and Landsat-8 data.
This parameter is optional.
Input8: Red edge image channel (0.732-0.748 um)
The image channel in the input file that contains the Sentinel-2 band called Vegetation Red Edge 2 (0.732-0.748 um).
Use this input specifically to calculate the CIedgeRed on Sentinel-2 data.
This parameter is optional.
Input9: Red edge image channel (0.773-0.793 um)
The image channel in the input file that contains the Sentinel-2 band called Vegetation Red Edge 3(0.773-0.793 um) band.
Use this input specifically to calculate the CIedgeRed on Sentinel-2 data.
This parameter is optional.
Input10: NIR image channel (0.855-0.875 um)
The image channel in the input file that contains the Sentinel-2 band called NIR (0.855-0.875 um) band.
Use this input specifically to calculate the MCARI2 data.
This parameter is optional.
Output: Generated vegetation indices
The output channel or channels to which to write the calculated vegetation index values.
If the output file is new, you need not specify a value for this parameter. VEGINDEX will write the results to 32-bit channels in the new file.
If the output file is an existing file, VEGINDEX will add new 32-bit channels to the file and write the index results to these channels
Index to calculate
The type of vegetation index to calculate. You can enter a single index or enter a comma-separated list of one or more.
To calculate all indices appropriate to the input data, select ALL.
Output type
The data type of the output channel to create.
When the number of output channels is greater than one, the specified data type is used for each output channel.
This parameter is optional.
Scaling offset
The scaling offset to convert the computed index values to digital numbers (DN) in the output image.
If you specify a value for this parameter, you must also specify a scaling-factor value.
Together, the scaling factor and scaling offset convert the computed radiance values to DNs, as follows:
DN = Reflectance × Scaling factor + Scaling offset
Gain = 1 ÷ Scaling factor
Bias = -Scaling offset ÷ Scaling factor
Scaling factor = 1 ÷ Gain
Scaling offset = -Bias ÷ Gain
This parameter is optional.
Scaling factor
The scaling factor to convert the computed index values to DNs in the output channels. The value or values you specify must be positive (greater than zero).
If you specify a value for the scaling factor, you must also specify a value for the scaling offset.
For information about scaling offset, including a list of default values according to data type, see the scaling-offset description.
This parameter is optional.
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VEGINDEX calculates one or more vegetation indices using the reflectance data (top of atmosphere (TOA) or absolute reflectance) in the input file, channels, or both. If the input data is DN values, they will be converted internally to TOA reflectance values for calculation. The results are written to a new file, or to the file and channels you specify.
To avoid scaling of the results produced by VEGINDEX, make sure they are written to 32-bit real channels.
When file and band metadata information is available, VEGINDEX uses this information to select appropriate data for the input index or indices.
Before running VEGINDEX, it is recommended that your input data be corrected atmospherically to ensure your results are due truly to the vegetation, and not changing atmospheric conditions.
Supported sensors
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These ratio images are derived from the absorption and reflection spectra of the material of interest. The absorption is based on the molecular bonds in the (surface) material. Therefore, the ratio often provides information on the chemical composition of the target.
The technique of ratioing bands involves separating the spectral-response value of a pixel in one image with that of the corresponding pixel in another. This is done to suppress similarities between bands and to eliminate albedo effects and shadows.
Vegetation indices
An assumption of vegetation indices is that all bare soil in an image will form a line in spectral space. Nearly all of the vegetation indices used commonly are concerned only with red-near-infrared space, so a red-near-infrared line for bare soil is assumed. This line is considered to be the line of zero vegetation.
All isovegetation lines converge at a single point.
The indices that use this assumption are the ratio-based indices, which measure the slope of the line between the point of convergence and the red-NIR point of the pixel. Some examples are: NDVI and RVI.
All isovegetation lines remain parallel to the bare soil line.
Typically, these indices are called perpendicular, because they measure the perpendicular distance from the soil line to the red-NIR point of the pixel. Examples are: DVI and PVI.
Most vegetation formulas are designed for use with data of three or more bands. The VEGINDEX algorithms are separated by the type of input data that is expected for each.
Sensors with RGB only
| Name | Algorithm |
|---|---|
| GRVI | (Green – Red) ÷ (Green + Red) |
| GI | ((2.0 × Green) - (Red + Blue)) ÷ ((2.0 × Green) + Red + Blue) |
Sensors with RGB and near-infrared (NIR)
| Name | Algorithm | Reference |
|---|---|---|
| VDI | NIR – Red | 10 |
| RVI | NIR ÷ Red | 2 |
| NDVI | (NIR – Red) ÷ (NIR + Red) | 9 |
| TDVI | (NIR – Red) ÷ (NIR + Red) + .51/2 | 1 |
| SAVI | ((NIR – Red) ÷ (NIR + Red + L)) × (1 + L)
The L value is based on the amount of green vegetative cover. With VEGINDEX, L is a default of 0.5, which means, generally, areas of moderate green vegetative cover. |
5 |
| MSAVI2 | (0.5) × (2(NIR + 1) – sqrt((2 × NIR + 1)2 – 8(NIR – Red))) | 8 |
| GEMI | eta × (1 – 0.25 × eta) – ((Red – 0.125) ÷ (1 – Red))
Where eta = (2 × (NIR2 – Red2) + 1.5 × NIR + 0.5 × Red) ÷ (NIR + Red + 0.5) |
7 |
| MTVI | 1.2 × [1.2 × (NIR – Green) – 2.5 × (Red – Green)] | 4 |
| EVI | 2.5 × (NIR – Red) ÷ (1+NIR+(6 ×Red) – (7.5 × Blue) | 11 |
| EVI2 | 2.5 × (NIR – Red) ÷ (NIR+(2.4 ×Red)+1) | 12 |
| OSAVI | (NIR – Red) ÷ (NIR+Red)+0.16) | 13 |
| MCARI2 | (1.5 ×[2.5 × (NIR – Red)] – [1.3 ×(NIR – Green)]) ÷ SQRT[((2 × NIR)+1)2 – ((6 ×NIR) – (5 × (SQRT(Red)))) – 0.5)] | 4 |
| LAI | (3.618 × EVI) – 0.118 | 22 |
Sensors with RGB, red edge and near-infrared (NIR) or shortwave infrared (SWIR)
| Name | Algorithm | Reference |
|---|---|---|
| GVI (Landsat-7 and Landsat-8 only) | (–0.2848*TM1) + (–0.2435*TM2) + (–0.5436*TM3) + (0.7243*TM4) + (0.0840*TM5) + (–1.1800*TM7) | 6 |
| MCARI | [(RedEdge – Red) – 0.2 × (RedEdge - Green)] × (RedEdge ÷ Red) | 3 |
| AFRI16 | [(NIR – (0.66 × SWIR1.6)) ÷ (NIR + (0.66 × SWIR1.6)); | 14 |
| AFRI21 | [(NIR – (0.5 × SWIR2.1)) ÷ (NIR + (0.5 × SWIR2.1)); | 14 |
| RENDVI (also known as NDRE) | (RedEdge750mm – NIR)) ÷ (RedEdge750mm+NIR); | 15 |
| MRENDVI | (RedEdge750mm – NIR)) ÷ (RedEdge750mm+NIR – (2 × Blue); | 16/17 |
| TCARI | 3 × (RedEdge700mm – Red) – (0.2 × (RedEdge700mm – Green) × (RedEdge700mm ÷ Red) | 18 |
| NMDI | (NIR860mm – (SWIR1.6 – SWIR2.1)) ÷ (NIR860mm + (SWIR1.6 –SWIR2.1)) | 19/20 |
| CIRedEdge | (RedEdge780mm ÷ RedEdge705mm) – 1 | 21 |
| NDNI | ((log(1 ÷ SWIR) – log(1 ÷ SWIR1)) ÷ (log(1 ÷ SWIR) – log(1 ÷ SWIR1))) | 23 |
| PSRI | ( (Red – Blue) ÷ RedEdge750mm | 24 |
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