torchgeo.transforms

TorchGeo transforms.

class torchgeo.transforms.AppendBNDVI(index_nir, index_blue)

Bases: AppendNormalizedDifferenceIndex

Blue Normalized Difference Vegetation Index (BNDVI).

Computes the following index:

\[\text{BNDVI} = \frac{\text{NIR} - \text{B}}{\text{NIR} + \text{B}}\]

If you use this index in your research, please cite the following paper:

• https://doi.org/10.1016/S1672-6308(07)60027-4

New in version 0.3.

__init__(index_nir, index_blue)

Initialize a new transform instance.

Parameters

• index_nir (int) – index of the NIR band, e.g. B8 in Sentinel 2 imagery

• index_blue (int) – index of the Blue band, e.g. B2 in Sentinel 2 imagery

class torchgeo.transforms.AppendGBNDVI(index_nir, index_green, index_blue)

Bases: AppendTriBandNormalizedDifferenceIndex

Green-Blue Normalized Difference Vegetation Index (GBNDVI).

Computes the following index:

\[\text{GBNDVI} = \frac{\text{NIR} - (\text{G} + \text{B})}{\text{NIR} + (\text{G} + \text{B})}\]

If you use this index in your research, please cite the following paper:

• https://doi.org/10.1016/S1672-6308(07)60027-4

New in version 0.3.

__init__(index_nir, index_green, index_blue)

Initialize a new transform instance.

Parameters

• index_nir (int) – index of the NIR band, e.g. B8 in Sentinel 2 imagery

• index_green (int) – index of the Green band, B3 in Sentinel 2 imagery

• index_blue (int) – index of the Blue band, B2 in Sentinel 2 imagery

class torchgeo.transforms.AppendGNDVI(index_nir, index_green)

Bases: AppendNormalizedDifferenceIndex

Green Normalized Difference Vegetation Index (GNDVI).

Computes the following index:

\[\text{GNDVI} = \frac{\text{NIR} - \text{G}}{\text{NIR} + \text{G}}\]

If you use this index in your research, please cite the following paper:

• https://doi.org/10.2134/agronj2001.933583x

New in version 0.3.

__init__(index_nir, index_green)

Initialize a new transform instance.

Parameters

• index_nir (int) – index of the NIR band, e.g. B8 in Sentinel 2 imagery

• index_green (int) – index of the Green band, e.g. B3 in Sentinel 2 imagery

class torchgeo.transforms.AppendGRNDVI(index_nir, index_green, index_red)

Bases: AppendTriBandNormalizedDifferenceIndex

Green-Red Normalized Difference Vegetation Index (GRNDVI).

Computes the following index:

\[\text{GRNDVI} = \frac{\text{NIR} - (\text{G} + \text{R})}{\text{NIR} + (\text{G} + \text{R})}\]

If you use this index in your research, please cite the following paper:

• https://doi.org/10.1016/S1672-6308(07)60027-4

New in version 0.3.

__init__(index_nir, index_green, index_red)

Initialize a new transform instance.

Parameters

• index_nir (int) – index of the NIR band, e.g. B8 in Sentinel 2 imagery

• index_green (int) – index of the Green band, B3 in Sentinel 2 imagery

• index_red (int) – index of the Red band, B4 in Sentinel 2 imagery

class torchgeo.transforms.AppendNBR(index_nir, index_swir)

Bases: AppendNormalizedDifferenceIndex

Normalized Burn Ratio (NBR).

Computes the following index:

\[\text{NBR} = \frac{\text{NIR} - \text{SWIR}}{\text{NIR} + \text{SWIR}}\]

If you use this index in your research, please cite the following paper:

• https://www.sciencebase.gov/catalog/item/4f4e4b20e4b07f02db6abb36

New in version 0.2.0.

__init__(index_nir, index_swir)

Initialize a new transform instance.

Parameters

• index_nir (int) – index of the Near Infrared (NIR) band in the image

• index_swir (int) – index of the Short-wave Infrared (SWIR) band in the image

class torchgeo.transforms.AppendNDBI(index_swir, index_nir)

Bases: AppendNormalizedDifferenceIndex

Normalized Difference Built-up Index (NDBI).

Computes the following index:

\[\text{NDBI} = \frac{\text{SWIR} - \text{NIR}}{\text{SWIR} + \text{NIR}}\]

If you use this index in your research, please cite the following paper:

• https://doi.org/10.1080/01431160304987

__init__(index_swir, index_nir)

Initialize a new transform instance.

Parameters

• index_swir (int) – index of the Short-wave Infrared (SWIR) band in the image

• index_nir (int) – index of the Near Infrared (NIR) band in the image

class torchgeo.transforms.AppendNDRE(index_nir, index_vre1)

Bases: AppendNormalizedDifferenceIndex

Normalized Difference Red Edge Vegetation Index (NDRE).

Computes the following index:

\[\text{NDRE} = \frac{\text{NIR} - \text{VRE1}}{\text{NIR} + \text{VRE1}}\]

If you use this index in your research, please cite the following paper:

• https://agris.fao.org/agris-search/search.do?recordID=US201300795763

New in version 0.3.

__init__(index_nir, index_vre1)

Initialize a new transform instance.

Parameters

• index_nir (int) – index of the NIR band, e.g. B8 in Sentinel 2 imagery

• index_vre1 (int) – index of the Red Edge band, B5 in Sentinel 2 imagery

class torchgeo.transforms.AppendNDSI(index_green, index_swir)

Bases: AppendNormalizedDifferenceIndex

Normalized Difference Snow Index (NDSI).

Computes the following index:

\[\text{NDSI} = \frac{\text{G} - \text{SWIR}}{\text{G} + \text{SWIR}}\]

If you use this index in your research, please cite the following paper:

• https://doi.org/10.1109/IGARSS.1994.399618

__init__(index_green, index_swir)

Initialize a new transform instance.

Parameters

• index_green (int) – index of the Green band in the image

• index_swir (int) – index of the Short-wave Infrared (SWIR) band in the image

class torchgeo.transforms.AppendNDVI(index_red, index_nir)

Bases: AppendNormalizedDifferenceIndex

Normalized Difference Vegetation Index (NDVI).

Computes the following index:

\[\text{NDVI} = \frac{\text{R} - \text{NIR}}{\text{R} + \text{NIR}}\]

If you use this index in your research, please cite the following paper:

• https://doi.org/10.1016/0034-4257(79)90013-0

__init__(index_red, index_nir)

Initialize a new transform instance.

Parameters

• index_red (int) – index of the Red band in the image

• index_nir (int) – index of the Near Infrared (NIR) band in the image

class torchgeo.transforms.AppendNDWI(index_green, index_nir)

Bases: AppendNormalizedDifferenceIndex

Normalized Difference Water Index (NDWI).

Computes the following index:

\[\text{NDWI} = \frac{\text{G} - \text{NIR}}{\text{G} + \text{NIR}}\]

If you use this index in your research, please cite the following paper:

• https://doi.org/10.1080/01431169608948714

__init__(index_green, index_nir)

Initialize a new transform instance.

Parameters

• index_green (int) – index of the Green band in the image

• index_nir (int) – index of the Near Infrared (NIR) band in the image

class torchgeo.transforms.AppendNormalizedDifferenceIndex(index_a, index_b)

Bases: Module

Append normalized difference index as channel to image tensor.

Computes the following index:

\[\text{NDI} = \frac{A - B}{A + B}\]

New in version 0.2.

__init__(index_a, index_b)

Initialize a new transform instance.

Parameters

• index_a (int) – reference band channel index

• index_b (int) – difference band channel index

forward(sample)

Compute and append normalized difference index to image.

Parameters

sample (Dict[str, Tensor]) – a sample or batch dict

Returns

the transformed sample

Return type

Dict[str, Tensor]

class torchgeo.transforms.AppendRBNDVI(index_nir, index_red, index_blue)

Bases: AppendTriBandNormalizedDifferenceIndex

Red-Blue Normalized Difference Vegetation Index (RBNDVI).

Computes the following index:

\[\text{RBNDVI} = \frac{\text{NIR} - (\text{R} + \text{B})}{\text{NIR} + (\text{R} + \text{B})}\]

If you use this index in your research, please cite the following paper:

• https://doi.org/10.1016/S1672-6308(07)60027-4

New in version 0.3.

__init__(index_nir, index_red, index_blue)

Initialize a new transform instance.

Parameters

• index_nir (int) – index of the NIR band, e.g. B8 in Sentinel 2 imagery

• index_red (int) – index of the Red band, B4 in Sentinel 2 imagery

• index_blue (int) – index of the Blue band, B2 in Sentinel 2 imagery

class torchgeo.transforms.AppendSWI(index_red, index_swir)

Bases: AppendNormalizedDifferenceIndex

Standardized Water-Level Index (SWI).

Computes the following index:

\[\text{SWI} = \frac{\text{R} - \text{SWIR}}{\text{R} + \text{SWIR}}\]

If you use this index in your research, please cite the following paper:

• https://doi.org/10.3390/w13121647

New in version 0.3.

__init__(index_red, index_swir)

Initialize a new transform instance.

Parameters

• index_red (int) – index of the VRE1 band, e.g. B5 in Sentinel 2 imagery

• index_swir (int) – index of the SWIR2 band, e.g. B11 in Sentinel 2 imagery

class torchgeo.transforms.AppendTriBandNormalizedDifferenceIndex(index_a, index_b, index_c)

Bases: Module

Append normalized difference index involving 3 bands as channel to image tensor.

Computes the following index:

\[\text{NDI} = \frac{A - (B + C)}{A + (B + C)}\]

New in version 0.3.

__init__(index_a, index_b, index_c)

Initialize a new transform instance.

Parameters

• index_a (int) – reference band channel index

• index_b (int) – difference band channel index of component 1

• index_c (int) – difference band channel index of component 2

forward(sample)

Compute and append tri-band normalized difference index to image.

Parameters

sample (Dict[str, Tensor]) – a sample or batch dict

Returns

the transformed sample

Return type

Dict[str, Tensor]

class torchgeo.transforms.AugmentationSequential(*args, data_keys)

Bases: Module

Wrapper around kornia AugmentationSequential to handle input dicts.

__init__(*args, data_keys)

Initialize a new augmentation sequential instance.

Parameters

• *args (Module) – Sequence of kornia augmentations

• data_keys (List[str]) – List of inputs to augment (e.g. [“image”, “mask”, “boxes”])

forward(sample)

Perform augmentations and update data dict.

Parameters

sample (Dict[str, Tensor]) – the input

Returns

the augmented input

Return type

Dict[str, Tensor]