Module: sarpyx.science.indices
File: sarpyx/science/indices.py
No module docstring available; module purpose is inferred from implementation.
Exported Symbols (__all__)
No explicit __all__ list. Public symbols inferred from implementation.
Public Functions (14)
calculate_rvi function
Calculates the Radar Vegetation Index (RVI) from Sentinel-1 dual-pol data.
File location: sarpyx/science/indices.py:4
Signature
calculate_rvi(sigma_vv, sigma_vh)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
sigma_vv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VV polarization. |
sigma_vh | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VH polarization. |
Return Type
inferred from implementation
np.ndarray: The Radar Vegetation Index (RVI) array. Returns NaN where denominator is zero or negative. References: - https://www.mdpi.com/2076-3417/9/4/655 - https://forum.step.esa.int/t/creating-radar-vegetation-index/12444/18
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.science.indices import calculate_rvi
result = calculate_rvi(sigma_vv=<sigma_vv>, sigma_vh=<sigma_vh>)Edge Cases
No explicit edge-case section found; behavior is inferred from implementation.
calculate_dpdd function
Calculates the Dual-Pol Diagonal Distance (DPDD) from Sentinel-1 dual-pol data.
File location: sarpyx/science/indices.py:36
Signature
calculate_dpdd(sigma_vv, sigma_vh)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
sigma_vv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VV polarization. |
sigma_vh | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VH polarization. |
Return Type
inferred from implementation
np.ndarray: The Dual-Pol Diagonal Distance (DPDD) array. References: - See documentation: https://www.sciencedirect.com/science/article/pii/S0034425718304140?via%3Dihub
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.science.indices import calculate_dpdd
result = calculate_dpdd(sigma_vv=<sigma_vv>, sigma_vh=<sigma_vh>)Edge Cases
No explicit edge-case section found; behavior is inferred from implementation.
calculate_dprvi_hh function
Calculates the Dual-Polarized Radar Vegetation Index HH (DpRVIHH) from radar data.
File location: sarpyx/science/indices.py:64
Signature
calculate_dprvi_hh(sigma_hh, sigma_hv)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
sigma_hh | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for HH polarization. |
sigma_hv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for HV polarization. |
Return Type
inferred from implementation
np.ndarray: The Dual-Polarized Radar Vegetation Index HH array. Returns NaN where denominator is zero or negative. References: - See documentation for full reference details: https://www.tandfonline.com/doi/abs/10.5589/m12-043
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.science.indices import calculate_dprvi_hh
result = calculate_dprvi_hh(sigma_hh=<sigma_hh>, sigma_hv=<sigma_hv>)Edge Cases
No explicit edge-case section found; behavior is inferred from implementation.
calculate_dprvi_vv function
Calculates the Dual-Polarized Radar Vegetation Index VV (DpRVIVV) from radar data.
File location: sarpyx/science/indices.py:95
Signature
calculate_dprvi_vv(sigma_vv, sigma_vh)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
sigma_vv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VV polarization. |
sigma_vh | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VH polarization. |
Return Type
inferred from implementation
np.ndarray: The Dual-Polarized Radar Vegetation Index VV array. Returns NaN where denominator is zero or negative. References: - See ref: https://www.mdpi.com/2076-3417/9/4/655
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.science.indices import calculate_dprvi_vv
result = calculate_dprvi_vv(sigma_vv=<sigma_vv>, sigma_vh=<sigma_vh>)Edge Cases
No explicit edge-case section found; behavior is inferred from implementation.
calculate_ndpoll function
Calculates the Normalized Difference Polarization Index (NDPoll).
File location: sarpyx/science/indices.py:126
Signature
calculate_ndpoll(sigma_vv, sigma_vh)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
sigma_vv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VV polarization. |
sigma_vh | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VH polarization. |
Return Type
inferred from implementation
np.ndarray: The NDPoll array. Returns NaN where the denominator is zero.
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.science.indices import calculate_ndpoll
result = calculate_ndpoll(sigma_vv=<sigma_vv>, sigma_vh=<sigma_vh>)Edge Cases
No explicit edge-case section found; behavior is inferred from implementation.
calculate_qprvi function
Calculates the Quad-Polarized Radar Vegetation Index (QpRVI).
File location: sarpyx/science/indices.py:152
Signature
calculate_qprvi(sigma_hh, sigma_vv, sigma_hv)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
sigma_hh | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for HH polarization. |
sigma_vv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VV polarization. |
sigma_hv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for HV polarization. |
Return Type
inferred from implementation
np.ndarray: The QpRVI array. Returns NaN where the denominator is zero.
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.science.indices import calculate_qprvi
result = calculate_qprvi(sigma_hh=<sigma_hh>, sigma_vv=<sigma_vv>, sigma_hv=<sigma_hv>)Edge Cases
No explicit edge-case section found; behavior is inferred from implementation.
calculate_rfdi function
Calculates the Radar Forest Degradation Index (RFDI).
File location: sarpyx/science/indices.py:180
Signature
calculate_rfdi(sigma_hh, sigma_hv)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
sigma_hh | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for HH polarization. |
sigma_hv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for HV polarization. |
Return Type
inferred from implementation
np.ndarray: The RFDI array. Returns NaN where the denominator is zero.
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.science.indices import calculate_rfdi
result = calculate_rfdi(sigma_hh=<sigma_hh>, sigma_hv=<sigma_hv>)Edge Cases
No explicit edge-case section found; behavior is inferred from implementation.
calculate_vddpi function
Calculates the Vertical Dual De-Polarization Index (VDDPI).
File location: sarpyx/science/indices.py:206
Signature
calculate_vddpi(sigma_vv, sigma_vh)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
sigma_vv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VV polarization. |
sigma_vh | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VH polarization. |
Return Type
inferred from implementation
np.ndarray: The VDDPI array. Returns NaN where VV is zero.
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.science.indices import calculate_vddpi
result = calculate_vddpi(sigma_vv=<sigma_vv>, sigma_vh=<sigma_vh>)Edge Cases
No explicit edge-case section found; behavior is inferred from implementation.
calculate_vhvvd function
Calculates the VH-VV Difference.
File location: sarpyx/science/indices.py:232
Signature
calculate_vhvvd(sigma_vh, sigma_vv)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
sigma_vh | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VH polarization. |
sigma_vv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VV polarization. |
Return Type
inferred from implementation
np.ndarray: The VH-VV Difference array.
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.science.indices import calculate_vhvvd
result = calculate_vhvvd(sigma_vh=<sigma_vh>, sigma_vv=<sigma_vv>)Edge Cases
No explicit edge-case section found; behavior is inferred from implementation.
calculate_vhvvp function
Calculates the VH-VV Product.
File location: sarpyx/science/indices.py:250
Signature
calculate_vhvvp(sigma_vh, sigma_vv)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
sigma_vh | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VH polarization. |
sigma_vv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VV polarization. |
Return Type
inferred from implementation
np.ndarray: The VH-VV Product array.
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.science.indices import calculate_vhvvp
result = calculate_vhvvp(sigma_vh=<sigma_vh>, sigma_vv=<sigma_vv>)Edge Cases
No explicit edge-case section found; behavior is inferred from implementation.
calculate_vhvvr function
Calculates the VH-VV Ratio.
File location: sarpyx/science/indices.py:268
Signature
calculate_vhvvr(sigma_vh, sigma_vv)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
sigma_vh | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VH polarization. |
sigma_vv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VV polarization. |
Return Type
inferred from implementation
np.ndarray: The VH-VV Ratio array. Returns NaN where VV is zero.
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.science.indices import calculate_vhvvr
result = calculate_vhvvr(sigma_vh=<sigma_vh>, sigma_vv=<sigma_vv>)Edge Cases
No explicit edge-case section found; behavior is inferred from implementation.
calculate_vvvhd function
Calculates the VV-VH Difference.
File location: sarpyx/science/indices.py:291
Signature
calculate_vvvhd(sigma_vv, sigma_vh)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
sigma_vv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VV polarization. |
sigma_vh | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VH polarization. |
Return Type
inferred from implementation
np.ndarray: The VV-VH Difference array.
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.science.indices import calculate_vvvhd
result = calculate_vvvhd(sigma_vv=<sigma_vv>, sigma_vh=<sigma_vh>)Edge Cases
No explicit edge-case section found; behavior is inferred from implementation.
calculate_vvvhr function
Calculates the VV-VH Ratio.
File location: sarpyx/science/indices.py:310
Signature
calculate_vvvhr(sigma_vv, sigma_vh)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
sigma_vv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VV polarization. |
sigma_vh | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VH polarization. |
Return Type
inferred from implementation
np.ndarray: The VV-VH Ratio array. Returns NaN where VH is zero.
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.science.indices import calculate_vvvhr
result = calculate_vvvhr(sigma_vv=<sigma_vv>, sigma_vh=<sigma_vh>)Edge Cases
No explicit edge-case section found; behavior is inferred from implementation.
calculate_vvvhs function
Calculates the VV-VH Sum.
File location: sarpyx/science/indices.py:333
Signature
calculate_vvvhs(sigma_vv, sigma_vh)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
sigma_vv | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VV polarization. |
sigma_vh | inferred from implementation | yes | - | Backscatter coefficient (linear scale) for VH polarization. |
Return Type
inferred from implementation
np.ndarray: The VV-VH Sum array.
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.science.indices import calculate_vvvhs
result = calculate_vvvhs(sigma_vv=<sigma_vv>, sigma_vh=<sigma_vh>)Edge Cases
No explicit edge-case section found; behavior is inferred from implementation.
Public Classes (0)
No public classes detected.