Algorithms and utilities for SAR sensors

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Last update: Dec 27, 2022

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Algorithms sarsen

Overview

WARNING: THIS CODE IS NOT READY FOR USE

Sarsen

Algorithms and utilities for SAR sensors

Objectives

Be faster and simpler than ESA SNAP and cloud native.

enable SAR data geocoding
- fast mode: to terrain-correct images
- accurate mode: for interferometric processing
enable radiometric terrain correction / flattening gamma
support cloud-native processing
- enable parallel processing via xarray and dask
- enable object storage access via fsspec
support Sentinel-1 SLC IW and GRD
support any DEM that GDAL / Proj can handle

Non-objectives

No attempt is done to support UTC leap seconds. Observations that include a leap second may crash the code or silently return wrong results. Caveat emptor

Usage

>>> import sarsen

Comments

sync with latest xarray

sarsen is not compatible with the latest (unreleased) xarray. I was able to report and fix a couple of issues upstream (https://github.com/pydata/xarray/issues/6597, https://github.com/pydata/xarray/issues/6600), but we need to apply a few changes in sarsen as well.

I tested with xarray@main commit c34ef8a60227720724e90aa11a6266c0026a812a, and all tests are successful.

Let me know if you would like me to add an action that (periodically?) runs the CI using the xarray version under development.

opened by malmans2 4
SARSEN Error

I have tested on both CentOS 7 and Windows 10. We are unable to use SARSEN because of this error: sarsen gtc S1A_IW_GRDH_1SDV_20210519T094926_20210519T094951_037955_047ACD_7336.zip "IW/VV" GLO20_WGS84_clipped.tif Traceback (most recent call last): File "/opt/anaconda3/envs/SARSEN/bin/sarsen", line 8, in sys.exit(app()) File "/opt/anaconda3/envs/SARSEN/lib/python3.10/site-packages/typer/main.py", line 214, in call return get_command(self)(*args, **kwargs) File "/opt/anaconda3/envs/SARSEN/lib/python3.10/site-packages/click/core.py", line 1128, in call return self.main(*args, **kwargs) File "/opt/anaconda3/envs/SARSEN/lib/python3.10/site-packages/click/core.py", line 1053, in main rv = self.invoke(ctx) File "/opt/anaconda3/envs/SARSEN/lib/python3.10/site-packages/click/core.py", line 1659, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "/opt/anaconda3/envs/SARSEN/lib/python3.10/site-packages/click/core.py", line 1395, in invoke return ctx.invoke(self.callback, **ctx.params) File "/opt/anaconda3/envs/SARSEN/lib/python3.10/site-packages/click/core.py", line 754, in invoke return __callback(*args, **kwargs) File "/opt/anaconda3/envs/SARSEN/lib/python3.10/site-packages/typer/main.py", line 500, in wrapper return callback(**use_params) # type: ignore File "/opt/anaconda3/envs/SARSEN/lib/python3.10/site-packages/sarsen/main.py", line 17, in gtc apps.backward_geocode_sentinel1( File "/opt/anaconda3/envs/SARSEN/lib/python3.10/site-packages/sarsen/apps.py", line 84, in backward_geocode_sentinel1 measurement_ds = xr.open_dataset( File "/opt/anaconda3/envs/SARSEN/lib/python3.10/site-packages/xarray/backends/api.py", line 495, in open_dataset backend_ds = backend.open_dataset( File "/opt/anaconda3/envs/SARSEN/lib/python3.10/site-packages/xarray_sentinel/xarray_backends.py", line 18, in open_dataset ds = sentinel1.open_sentinel1_dataset( File "/opt/anaconda3/envs/SARSEN/lib/python3.10/site-packages/xarray_sentinel/sentinel1.py", line 715, in open_sentinel1_dataset product_attrs, product_files = esa_safe.parse_manifest_sentinel1(file) File "/opt/anaconda3/envs/SARSEN/lib/python3.10/site-packages/xarray_sentinel/esa_safe.py", line 111, in parse_manifest_sentinel1 manifest = ElementTree.parse(manifest_path) File "/opt/anaconda3/envs/SARSEN/lib/python3.10/xml/etree/ElementTree.py", line 1229, in parse tree.parse(source, parser) File "/opt/anaconda3/envs/SARSEN/lib/python3.10/xml/etree/ElementTree.py", line 580, in parse self._root = parser._parse_whole(source) xml.etree.ElementTree.ParseError: not well-formed (invalid token): line 1, column 2

opened by S0sh0rt 3
Use gamma-0 backscatter convention for RTC output

Hi all, I was wondering why you chose to stick to the beta-0 backscatter convention instead of gamma-0 for the RTC output? Isn't the entire point of applying David Small's RTC algorithm [1] to get a terrain-flattened, gamma-0 normalized backscatter product? Furthermore, you might have heard of the CEOS CARD4L Normalised Radar Backscatter specification [2], which also endorses the gamma-0 backscatter convention.

Great software and I'm looking forward to hearing from you!

[1] https://doi.org/10.1109/tgrs.2011.2120616 [2] https://ceos.org/ard/files/PFS/NRB/v5.5/CARD4L-PFS_NRB_v5.5.pdf

opened by maawoo 2
Radiometric terrain-correction algorithm is slow and memory hungry
At the minimum:

[x] review what step can be simplified

[x] review in what step we may reduce memory pressure by moving computations to dask out-of-core

performance
opened by alexamici 2
Bump mamba-org/provision-with-micromamba from 13 to 14
Bumps mamba-org/provision-with-micromamba from 13 to 14.

Release notes

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v14

What's Changed

Add micromamba deinit in post.js by @pavelzw in mamba-org/provision-with-micromamba#89

Fix duplicate options by @jonashaag in mamba-org/provision-with-micromamba#98

New Contributors

@pavelzw made their first contribution in mamba-org/provision-with-micromamba#89

Full Changelog: https://github.com/mamba-org/provision-with-micromamba/compare/v13...v14

Commits

f347426 Remove unnecessary options (#98)

e542c7a Update deps (#93)

8aa0e58 Update actions/checkout (#91)

b54d7bb Add micromamba deinit in post.js (#89)

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dependencies
opened by dependabot[bot] 1
Bump mamba-org/provision-with-micromamba from 12 to 13
Bumps mamba-org/provision-with-micromamba from 12 to 13.

Release notes

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v13

Fix channels and channel-priority settings

Support linux-aarch64 and osx-arm64 runners

Support sel(unix)

Commits

a319a81 Readme updates (#88)

28fa105 add unix for condaArch linux or osx (#85)

bc8e4cc Fix channel priority (#84)

52dc9e6 Delete dist/post.js directory (#83)

87a13a6 use "channels" and not extraChannels (#82)

e198969 Fix await (#78)

d90963f Refactoring (#73)

431e55a Add timeouts to GHA workflows (#74)

21e0d20 Merge pull request #71 from mamba-org/aarch64

23fc0a3 Fix mac

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dependencies
opened by dependabot[bot] 1
Bump codecov/codecov-action from 3.1.0 to 3.1.1
Bumps codecov/codecov-action from 3.1.0 to 3.1.1.

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3.1.1

What's Changed

Update deprecation warning by @slifty in codecov/codecov-action#661

Create codeql-analysis.yml by @mitchell-codecov in codecov/codecov-action#593

build(deps): bump node-fetch from 3.2.3 to 3.2.4 by @dependabot in codecov/codecov-action#714

build(deps-dev): bump typescript from 4.6.3 to 4.6.4 by @dependabot in codecov/codecov-action#713

README: fix typo by @Evalir in codecov/codecov-action#712

build(deps): bump github/codeql-action from 1 to 2 by @dependabot in codecov/codecov-action#724

build(deps-dev): bump @types/jest from 27.4.1 to 27.5.0 by @dependabot in codecov/codecov-action#717

fix: Remove a blank row by @johnmanjiro13 in codecov/codecov-action#725

Update README.md with correct badge version by @gsheni in codecov/codecov-action#726

build(deps-dev): bump @types/node from 17.0.25 to 17.0.33 by @dependabot in codecov/codecov-action#729

build(deps-dev): downgrade @types/node to 16.11.35 by @dependabot in codecov/codecov-action#734

build(deps): bump actions/checkout from 2 to 3 by @dependabot in codecov/codecov-action#723

build(deps): bump @actions/github from 5.0.1 to 5.0.3 by @dependabot in codecov/codecov-action#733

build(deps): bump @actions/core from 1.6.0 to 1.8.2 by @dependabot in codecov/codecov-action#732

build(deps-dev): bump @types/node from 16.11.35 to 16.11.36 by @dependabot in codecov/codecov-action#737

Create scorecards-analysis.yml by @mitchell-codecov in codecov/codecov-action#633

build(deps): bump ossf/scorecard-action from 1.0.1 to 1.1.0 by @dependabot in codecov/codecov-action#749

fix: add more verbosity to validation by @thomasrockhu-codecov in codecov/codecov-action#747

build(deps-dev): bump typescript from 4.6.4 to 4.7.3 by @dependabot in codecov/codecov-action#755

Regenerate scorecards-analysis.yml by @mitchell-codecov in codecov/codecov-action#750

build(deps-dev): bump @types/node from 16.11.36 to 16.11.39 by @dependabot in codecov/codecov-action#759

build(deps-dev): bump @types/node from 16.11.39 to 16.11.40 by @dependabot in codecov/codecov-action#762

build(deps-dev): bump @vercel/ncc from 0.33.4 to 0.34.0 by @dependabot in codecov/codecov-action#746

build(deps): bump ossf/scorecard-action from 1.1.0 to 1.1.1 by @dependabot in codecov/codecov-action#757

build(deps): bump openpgp from 5.2.1 to 5.3.0 by @dependabot in codecov/codecov-action#760

build(deps): bump actions/upload-artifact from 2.3.1 to 3.1.0 by @dependabot in codecov/codecov-action#748

build(deps-dev): bump typescript from 4.7.3 to 4.7.4 by @dependabot in codecov/codecov-action#766

Switch to v3 by @thomasrockhu in codecov/codecov-action#774

Fix network entry in table by @kevmoo in codecov/codecov-action#783

Trim arguments after splitting them by @mitchell-codecov in codecov/codecov-action#791

build(deps): bump openpgp from 5.3.0 to 5.4.0 by @dependabot in codecov/codecov-action#799

build(deps): bump @actions/core from 1.8.2 to 1.9.1 by @dependabot in codecov/codecov-action#798

Plumb failCi into verification function. by @RobbieMcKinstry in codecov/codecov-action#769

release: update changelog and version to 3.1.1 by @thomasrockhu-codecov in codecov/codecov-action#828

New Contributors

@slifty made their first contribution in codecov/codecov-action#661

@Evalir made their first contribution in codecov/codecov-action#712

@johnmanjiro13 made their first contribution in codecov/codecov-action#725

@gsheni made their first contribution in codecov/codecov-action#726

@kevmoo made their first contribution in codecov/codecov-action#783

@RobbieMcKinstry made their first contribution in codecov/codecov-action#769

Full Changelog: https://github.com/codecov/codecov-action/compare/v3.1.0...v3.1.1

Changelog

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3.1.1

Fixes

#661 Update deprecation warning

#593 Create codeql-analysis.yml

#712 README: fix typo

#725 fix: Remove a blank row

#726 Update README.md with correct badge version

#633 Create scorecards-analysis.yml

#747 fix: add more verbosity to validation

#750 Regenerate scorecards-analysis.yml

#774 Switch to v3

#783 Fix network entry in table

#791 Trim arguments after splitting them

#769 Plumb failCi into verification function.

Dependencies

#713 build(deps-dev): bump typescript from 4.6.3 to 4.6.4

#714 build(deps): bump node-fetch from 3.2.3 to 3.2.4

#724 build(deps): bump github/codeql-action from 1 to 2

#717 build(deps-dev): bump @types/jest from 27.4.1 to 27.5.0

#729 build(deps-dev): bump @types/node from 17.0.25 to 17.0.33

#734 build(deps-dev): downgrade @types/node to 16.11.35

#723 build(deps): bump actions/checkout from 2 to 3

#733 build(deps): bump @actions/github from 5.0.1 to 5.0.3

#732 build(deps): bump @actions/core from 1.6.0 to 1.8.2

#737 build(deps-dev): bump @types/node from 16.11.35 to 16.11.36

#749 build(deps): bump ossf/scorecard-action from 1.0.1 to 1.1.0

#755 build(deps-dev): bump typescript from 4.6.4 to 4.7.3

#759 build(deps-dev): bump @types/node from 16.11.36 to 16.11.39

#762 build(deps-dev): bump @types/node from 16.11.39 to 16.11.40

#746 build(deps-dev): bump @vercel/ncc from 0.33.4 to 0.34.0

#757 build(deps): bump ossf/scorecard-action from 1.1.0 to 1.1.1

#760 build(deps): bump openpgp from 5.2.1 to 5.3.0

#748 build(deps): bump actions/upload-artifact from 2.3.1 to 3.1.0

#766 build(deps-dev): bump typescript from 4.7.3 to 4.7.4

#799 build(deps): bump openpgp from 5.3.0 to 5.4.0

#798 build(deps): bump @actions/core from 1.8.2 to 1.9.1

Commits

d9f34f8 release: update changelog and version to 3.1.1 (#828)

0e9e7b4 Plumb failCi into verification function. (#769)

7f20bd4 build(deps): bump @actions/core from 1.8.2 to 1.9.1 (#798)

13bc253 build(deps): bump openpgp from 5.3.0 to 5.4.0 (#799)

5c0da1b Trim arguments after splitting them (#791)

68d5f6d Fix network entry in table (#783)

2a829b9 Switch to v3 (#774)

8e09eaf build(deps-dev): bump typescript from 4.7.3 to 4.7.4 (#766)

39e2229 build(deps): bump actions/upload-artifact from 2.3.1 to 3.1.0 (#748)

b2b7703 build(deps): bump openpgp from 5.2.1 to 5.3.0 (#760)

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dependencies
opened by dependabot[bot] 0
Add option to save the simulated image in SAR and geographic geometries

This is primarily intended as a development tool, as artefacts are more easily detectable on the simulated image, than on the RTC. It may as well allow more precise coregistration between the DEM and the image.

opened by alexamici 0
Make processing dask-friendly to allow larger-than-memory and parallel processing
Almost all operations can be chunked via the DEM chunks (not the image ones).

This includes:

[x] allow controlling the DEM chunks

[ ] use dask-friendly xarray-sentinel helpers

[ ] make internal functions (that need it) dask-friendly via xarray.map_blocks

[ ] add borders to the gamma flattening processing to avoid "seeing" the borders of the blocks

The main source of dask-unfriendliness is the wide spread use of DataArray.interp with the target values on the DEM coordinates. All operations (except the gamma flattening) can be performed on ("x", "y") blocks exactly.
enhancement
opened by alexamici 0
Bump codecov/codecov-action from 3.0.0 to 3.1.0
Bumps codecov/codecov-action from 3.0.0 to 3.1.0.

Release notes

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v3.1.0

3.1.0

Features

#699 Incorporate xcode arguments for the Codecov uploader

Dependencies

#694 build(deps-dev): bump @vercel/ncc from 0.33.3 to 0.33.4

#696 build(deps-dev): bump @types/node from 17.0.23 to 17.0.25

#698 build(deps-dev): bump jest-junit from 13.0.0 to 13.2.0

Changelog

Sourced from codecov/codecov-action's changelog.

3.1.0

Features

#699 Incorporate xcode arguments for the Codecov uploader

Dependencies

#694 build(deps-dev): bump @vercel/ncc from 0.33.3 to 0.33.4

#696 build(deps-dev): bump @types/node from 17.0.23 to 17.0.25

#698 build(deps-dev): bump jest-junit from 13.0.0 to 13.2.0

Commits

81cd2dc Merge pull request #699 from codecov/feat-xcode

a03184e feat: add xcode support

6a6a9ae Merge pull request #694 from codecov/dependabot/npm_and_yarn/vercel/ncc-0.33.4

92a872a Merge pull request #696 from codecov/dependabot/npm_and_yarn/types/node-17.0.25

43a9c18 Merge pull request #698 from codecov/dependabot/npm_and_yarn/jest-junit-13.2.0

13ce822 Merge pull request #690 from codecov/ci-v3

4d6dbaa build(deps-dev): bump jest-junit from 13.0.0 to 13.2.0

98f0f19 build(deps-dev): bump @types/node from 17.0.23 to 17.0.25

d3021d9 build(deps-dev): bump @vercel/ncc from 0.33.3 to 0.33.4

2c83f35 Update makefile to v3

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dependencies
opened by dependabot[bot] 0
QST: How to use sarsen functions on other SAR constellations than S1

Hello,

I would like to use sarsen to avoid using ESA SNAP in eoreader, but since this library lacks an API documentation, I have some questions 😄

I already have my own way to load agnostically these SAR constellations:

| Constellations | | --- | | COSMO-SkyMed 1st Generation | | COSMO-SkyMed 2nd Generation | | ICEYE | | RADARSAT Constellation Mission | | RADARSAT-2 | | Sentinel-1 | | SAOCOM-1 | | TerraSAR-X, TanDEM-X, PAZ SAR|

I would like to use your calibration, terrain correction (and so on) methods in order to avoid calling GPT. Is this already possible? (are they fundamentally sensor agnostic ?) Is this a good way to use of your library ? It seems your algorithms are based on xarray-sentinel, but is there a workaround to your functions that would allow anyone to give bands and metadata, allowing the user to easily use your library with other constellations ?

opened by remi-braun 4
DEM format requirements / Reproducible example

Hi all, I'm running into issues processing an SLC scene. Both GTC and RTC results are not really usable. I suspect my DEM is the problem and I'm wondering why, because I'm using the same DEM to successfully create an RTC product with SNAP. Here is the gdalinfo output if you're interested.

Can you provide some guidelines on format requirements for the DEM? Or at least a reproducible example in the notebook section. download_data.sh could, for example, be extended by a section that downloads DEM tiles from an open source (e.g., here) and prepares it with GDAL in the way sarsen expects.

Cheers, Marco

opened by maawoo 2
Add an option to crop the original product to allow fast testing

At the moment GitHub Actions on simple operation fail with a memory error, apparently due to the large size of the input image, even when opened with blocks.
enhancement

opened by alexamici 0
Local incidence angle images

Hi, I recently discovered sarsen. This is a great tool that fills an important gap in the python geo/rs stack! Thanks!

I have started to poke around to generate local incidence angle images for GRD products on a target CRS (the one of the DEM), the goal being to have a corrected (geometry and radiometry) SAR image + the local incidence angle (LIA) as a single stack with 3 channels (VV, VH, LIA).

Actually, I would only need the incidence angle array extracted with xarray-sentinel1 (your other lib) orthorectified on the DEM and then I could use the DEM slope and aspect to compute the local angle.

Could you give me some guidance in how to generate the incidence angle grid on the DEM geometry? I can't wrap my head around how to use the sarsen API once I get the incidence angles from the gcp subgroup from xarray-sentinel1.

Thank you.

opened by inglada 0

Releases(v0.9.3)

v0.9.3(Nov 1, 2022)

Minor release with the start of the abstraction of the input product detail into a generic SarProduct interface.
Source code(tar.gz)
Source code(zip)
v0.9.2(Jul 27, 2022)
Algorithms and utilities for Synthetic Aperture Radar (SAR) sensors. Enables cloud-native SAR processing via Xarray and Dask.

This Open Source project is sponsored by B-Open - https://www.bopen.eu.

Features and limitations

Sarsen is a Python library and command line tool with the following functionalities:

provides algorithms to terrain-correct satellite SAR data

geometric terrain correction (geocoding)

fast mode: to terrain-correct images

accurate mode: for interferometric processing

radiometric terrain correction (gamma flattening)

accesses SAR data via xarray-sentinel:

supports most Sentinel-1 data products as distributed by ESA:

Sentinel-1 Single Look Complex (SLC) SM/IW/EW

Sentinel-1 Ground Range Detected (GRD) SM/IW/EW

reads uncompressed and compressed SAFE data products on the local computer or on a network via fsspec - depends on rasterio>=1.3

accesses DEM data via rioxarray:

reads local and remote data in virtually any raster format via rasterio / GDAL

supports larger-than-memory and distributed data access and processing via Dask

efficient geometric terrain-correction for a full GRD

efficient radiometric terrain-correction for a full GRD.

Overall, the software is in the beta phase and the usual caveats apply.
Source code(tar.gz)
Source code(zip)
v0.9.0(Apr 26, 2022)
Algorithms and utilities for Synthetic Aperture Radar (SAR) sensors. Enables cloud-native SAR processing via Xarray and Dask.

This Open Source project is sponsored by B-Open - https://www.bopen.eu.

Features and limitations

Sarsen is a Python library and command line tool with the following functionalities:

provides algorithms to terrain-correct satellite SAR data

geometric terrain correction (geocoding)

fast mode: to terrain-correct images

accurate mode: for interferometric processing

radiometric terrain correction (gamma flattening)

accesses SAR data via xarray-sentinel:

supports most Sentinel-1 data products as distributed by ESA:

Sentinel-1 Single Look Complex (SLC) SM/IW/EW

Sentinel-1 Ground Range Detected (GRD) SM/IW/EW

reads uncompressed and compressed SAFE data products on the local computer or on a network via fsspec - depends on rasterio>=1.3a3

accesses DEM data via rioxarray:

reads local and remote data in virtually any raster format via rasterio / GDAL

supports larger-than-memory and distributed data access and processing via Dask

Overall, the software is in the beta phase and the usual caveats apply.
Source code(tar.gz)
Source code(zip)
v0.1(Mar 21, 2022)
Algorithms and utilities for Synthetic Aperture Radar (SAR) sensors. Enables cloud-native SAR processing via Xarray and Dask.

This Open Source project is sponsored by B-Open - https://www.bopen.eu.

Overall, the software is in the alpha phase and the usual caveats apply.

Features and limitations

Sarsen is a Python library and command line tool with the following functionalities:

provides algorithms to terrain-correct satellite SAR data

geometric terrain correction (geocoding)

fast mode: to terrain-correct images

accurate mode: for interferometric processing

radiometric terrain correction (gamma flattening)

accesses SAR data via xarray-sentinel:

supports all Sentinel-1 data products as distributed by ESA:

Sentinel-1 Single Look Complex (SLC) SM/IW/EW

Sentinel-1 Ground Range Detected (GRD) SM/IW/EW

reads uncompressed and compressed SAFE data products on the local computer or on a network via fsspec - depends on rasterio>=1.3a3

accesses DEM data via rioxarray:

reads local and remote data in virtually any raster format via rasterio / GDAL

supports larger-than-memory and distributed data access and processing via dask

Current limitations and work-in-progress items:

little-to-no documentation. See #6.

radiometric terrain-correction algorithm slow and memory hungry. See #7.

Source code(tar.gz)
Source code(zip)
v0.0.13(Mar 9, 2022)

Source code(tar.gz)
Source code(zip)

Owner

B-Open

GitHub

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Cormen-Lib - An academic tool for data structures and algorithms courses

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12 Aug 18, 2022

Algorithms and utilities for SAR sensors

Related tags

Overview

Sarsen

Objectives

Non-objectives

Usage

Comments

v14

What's Changed

New Contributors

v13

3.1.1

What's Changed

New Contributors

3.1.1

Fixes

Dependencies

v3.1.0

3.1.0

Features

Dependencies

3.1.0

Features

Dependencies

Releases(v0.9.3)

v0.9.3(Nov 1, 2022)

v0.9.2(Jul 27, 2022)

v0.9.0(Apr 26, 2022)

v0.1(Mar 21, 2022)

v0.0.13(Mar 9, 2022)

Owner

B-Open

Genetic algorithms are heuristic search algorithms inspired by the process that supports the evolution of life.

Algorithms and data structures for educational, demonstrational and experimental purposes.

Minimal examples of data structures and algorithms in Python

Repository for data structure and algorithms in Python for coding interviews

:computer: Data Structures and Algorithms in Python

Solving a card game with three search algorithms: BFS, IDS, and A*

Planning Algorithms in AI and Robotics. MSc course at Skoltech Data Science program

My dynamic programming algorithms for exercise and fun

CLI Eight Puzzle mini-game featuring BFS, DFS, Greedy and A* searches as solver algorithms.

Distributed algorithms, reimplemented for fun and practice

Python Client for Algorithmia Algorithms and Data API

Classic algorithms including Fizz Buzz, Bubble Sort, the Fibonacci Sequence, a Sudoku solver, and more.

Sorting-Algorithms - All information about sorting algorithm you need and you can visualize the code tracer

Cormen-Lib - An academic tool for data structures and algorithms courses

BCI datasets and algorithms

All Algorithms implemented in Python

Algorithms implemented in Python

A command line tool for memorizing algorithms in Python by typing them.

Python sample codes for robotics algorithms.