eoreader

Remote-sensing opensource python library reading optical and SAR sensors, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.

https://github.com/sertit/eoreader

Science Score: 59.0%

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Low similarity (7.6%) to scientific vocabulary

Keywords

cosmo-skymed earth-observation geopandas iceye landsat maxar planetscope pleiades radarsat rasterio remote-sensing saocom sar satellite-imagery sentinel-1 sentinel-2 sentinel-3 terrasar worldview xarray

Keywords from Contributors

labels astronomy parameter-estimation transformers jupyterlab climate-science

Last synced: 5 months ago · JSON representation

Repository

Remote-sensing opensource python library reading optical and SAR sensors, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.

Basic Info

Host: GitHub
Owner: sertit
License: apache-2.0
Language: Python
Default Branch: main
Homepage: https://eoreader.readthedocs.io/stable/
Size: 64.6 MB

Statistics

Stars: 316
Watchers: 5
Forks: 32
Open Issues: 43
Releases: 60

Topics

Created almost 5 years ago · Last pushed 6 months ago

Metadata Files

Readme Changelog Contributing License Code of conduct

README.md

EOReader

EOReader is a remote-sensing opensource python library reading optical and SAR constellations, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.

[!IMPORTANT] 💡 The goal of this library is to manage one satellite product at a time.
To handle more complicated sets of products (such as mosaics, pairs or time series), please consider using EOSets.

🛰️ Managed constellations

Optical

SAR

🔮 Features

EOReader implements sensor-agnostic features:

load: Load many band types:
- satellite bands (optical or SAR)
- index
- cloud bands
- DEM bands
stack: Stack all these type of bands

EOReader works mainly with: - xarrays.DataArray and xarrays.Dataset for raster data - geopandas.GeoDataFrames for vector data (extents, footprints...)

EOReader allow you to create internal STAC catalogs directly from raw data.

[!NOTE] 💡 EOReader handles data from the past!
Legacy format are mostly supported and if not, they can be requested by creating an issue with the legacy_format label.
This is super useful if you need to create an internal STAC catalog with old data.

⚡️ Quickstart

Optical

EOReader allows you ta load and stack spectral bands, spetrcal indices, DEM and cloud bands agnostically from every handled optical constellation:

```python from eoreader.reader import Reader from eoreader.bands import RED, GREEN, BLUE, NDVI, CLOUDS

Sentinel-2 path

s2path = "S2BMSIL1C20181126T022319N0207R103T51PWM_20181126T050025.SAFE"

Create the reader object and open satellite data

reader = Reader()

The reader will recognize the constellation from its product structure

s2prod = reader.open(s2path)

Load some bands and index

bands = s2_prod.load([NDVI, GREEN, CLOUDS])

Create a stack with some bands

stack = s2prod.stack([RED, GREEN, BLUE], stackpath="s2rgbstack.tif") ```

EOReader aligns spectral bands from every handled sensor in order to make any call to a band generic:

SAR

In the same way, you can import and stack radar band from any handled SAR constellation, with the same pattern.

```python from eoreader.reader import Reader from eoreader.bands import VV, VH, VVDSPK, VHDSPK

Sentinel-1 GRD path

s1path = "S1BEWGRDM1SDH20200422T08045920200422T080559021254028559_784D.zip"

Create the reader object and open satellite data

reader = Reader()

The reader will recognize the constellation from its product structure

s1prod = reader.open(s1path)

Load some bands and index

bands = s1_prod.load([VV, VH])

Create a stack with some bands

stack = s1prod.stack([VVDSPK, VHDSPK], stackpath="s1_stack.tif") ```

[!WARNING] ⚠️SNAP and SAR

SAR products need ESA SNAP free software to be orthorectified and calibrated. Ensure that you have the folder containing your gpt executable in your PATH. If you are using SNAP 8.0, be sure to have your software up-to-date (SNAP version >= 8.0).

📖 Documentation

The API documentation can be found here.

🔗 Examples

Available notebooks provided as examples:

Why EOReader?

Basics

Advanced

Experimental

Dask
STAC

🛠 Installation

Pip

You can install EOReader via pip:

pip install eoreader

EOReader mainly relies on geopandas, xarray and rasterio (through rioxarray).

Please look at the rasterio page to learn more about that.

Conda

You can install EOReader via conda:

conda config --env --set channel_priority strict conda install -c conda-forge eoreader

📚 Context

As one of the Copernicus Emergency Management Service Rapid Mapping and Risk and Recovery Mapping operators, SERTIT needs to deliver geoinformation (such as flood or fire delineation, landslides mapping, etc.) based on multiple EO constellations.

In rapid mapping, it is always important to have access to various sensor types, resolutions, and satellites. Indeed, SAR sensors are able to detect through clouds and during nighttime (which is particularly useful during flood and storm events), while optical sensors benefit from of multi spectral bands to better analyze and classify the crisis information.

As every minute counts in the production of geoinformation in an emergency mode, it seemed crucial to harmonize the ground on which are built our production tools, in order to make them as sensor-agnostic as possible.

This is why SERTIT decided to decouple the sensor handling from the extraction algorithms: the latter should be able to ingest semantic bands (i.e. RED or VV) without worrying about how to load the specific sensor band or in what unit it is.
The assumption was made that all the spectral bands from optical sensors could be mapped between each other, in addition to the natural mapping between SAR bands.

Thus, thanks to EOReader, these tools are made independent to the constellation:
✅ the algorithm (and its developer) can focus on its core tasks (such as extraction) without taking into account the sensor characteristics (how to load a band, which band correspond to which band number, …)
✅ new sensor addition is effortless (if existing in EOReader) and requires no algorithm modification
✅ maintenance is simplified and the code quality is significantly improved
✅ testing is also simplified as the sensor-related parts are tested in EOReader library

However, keep in mind that the support of all the constellations used in CEMS is done in the best effort mode, especially for commercial data. Indeed, we may not have faced every product type, sensor mode or order configuration, so some details may be missing. If this happens to you, do not hesitate to make a PR or write an issue about that!

🎤 Communication

Talks

GeoPython 2022 [ PDF ] [ YouTube ]
Mentioned in [Live+]SIG 2022 by ESRI France (in French): Enrichir ArcgisPro grâce à des processus personnalisés d'observation de la Terre [ PDF ]
Mentioned in GeoPython 2023 - FLORIA, a custom python pipeline for urban flood extraction from SAR multi-sensors, supported by U-Net convolutional network.
Mentioned in EGU 2023 - Cutting-edge developments in rapid mapping
FOSS4G 2023 [ PDF ] [ YouTube ]

Press Release

ESA Success Story
Used to extract water for assessing agriculture impacts after the Kakhovka Dam Collapse (cross-post from NASA Harvest and Planet)

Articles

Maxant, J. Braun, R. Caspard, M. Clandillon, S. ExtractEO, a Pipeline for Disaster Extent Mapping in the Context of Emergency Management. Remote Sens. 2022, 14, 5253. (Technical Note)

Blog

📝 License

EOReader is licensed under Apache License v2.0. See LICENSE file for details.

🖋️ Authors

EOReader has been created by ICube-SERTIT.

🤝 Credits

EOReader is built on top of amazing libs, without which it couldn't have been coded:

Owner

Name: ICube-SERTIT
Login: sertit
Kind: organization
Location: Strasbourg, France

Website: https://sertit.unistra.fr/
Repositories: 3
Profile: https://github.com/sertit

ICube-SERTIT's repository

GitHub Events

Total

Create event: 15
Issues event: 55
Release event: 10
Watch event: 37
Delete event: 4
Issue comment event: 78
Push event: 178
Pull request review comment event: 4
Pull request review event: 8
Pull request event: 38
Fork event: 10

Last Year

Create event: 15
Issues event: 55
Release event: 10
Watch event: 37
Delete event: 4
Issue comment event: 78
Push event: 179
Pull request review comment event: 4
Pull request review event: 8
Pull request event: 38
Fork event: 10

Committers

Last synced: 6 months ago

All Time

Total Commits: 1,619
Total Committers: 13
Avg Commits per committer: 124.538
Development Distribution Score (DDS): 0.06

Past Year

Commits: 315
Committers: 9
Avg Commits per committer: 35.0
Development Distribution Score (DDS): 0.149

Top Committers

Name	Email	Commits
BRAUN REMI	r**n@u**r	1,522
pre-commit-ci[bot]	6**]@u**m	28
jteulade	j**e@g**m	14
Michal Parusinski	p**i@u**r	12
Arthur VINCENT	a**t@c**u	10
guillemc23	g**5@g**m	8
CORIAT BASTIEN	b**t@u**r	7
Jayanth Siddamsetty	j**y@d**e	6
dependabot[bot]	4**]@u**m	5
Emmanuel Ferdman	e**n@g**m	3
TabeaW	3**W@u**m	2
Rémi Braun	6**n@u**m	1
floriandeboissieu	f**s@g**m	1

Committer Domains (Top 20 + Academic)

unistra.fr: 3 dfki.de: 1 csgroup.eu: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 155
Total pull requests: 93
Average time to close issues: 3 months
Average time to close pull requests: 18 days
Total issue authors: 21
Total pull request authors: 11
Average comments per issue: 1.98
Average comments per pull request: 0.65
Merged pull requests: 78
Bot issues: 0
Bot pull requests: 39

Past Year

Issues: 44
Pull requests: 36
Average time to close issues: 12 days
Average time to close pull requests: 2 days
Issue authors: 6
Pull request authors: 6
Average comments per issue: 0.73
Average comments per pull request: 0.75
Merged pull requests: 30
Bot issues: 0
Bot pull requests: 22

View more stats

Top Authors

Issue Authors

remi-braun (104)
jteulade (21)
ArthurVincentCS (5)
TK12331 (4)
BastienKovac (3)
bastiencyr (2)
oscarn2 (2)
sorny92 (1)
jaimebayes (1)
ChangpeiHe (1)
paron2407 (1)
jsetty (1)
guillemc23 (1)
funny000 (1)
zoepapirer (1)

Pull Request Authors

pre-commit-ci[bot] (32)
jteulade (20)
remi-braun (14)
guillemc23 (8)
dependabot[bot] (7)
ArthurVincentCS (2)
jsetty (2)
TabeaW (2)
bastiencyr (2)
emmanuel-ferdman (2)
floriandeboissieu (2)

Top Labels

Issue Labels

enhancement (56) bug (34) 0.22.0 (18) community driven (13) new product (9) 0.20.0 (7) optimization (6) 0.23.0 (5) 0.21.0 (5) documentation (5) wontfix (5) help wanted (5) needs detail (2) upstream (2) 1.0.0 (2) need sample (2) how to (2) installation (1) waiting upstream (1)

Pull Request Labels

dependencies (7) github_actions (3)

Packages

Total packages: 3
Total downloads:
- pypi 4,742 last-month

Total dependent packages: 3
(may contain duplicates)
Total dependent repositories: 4
(may contain duplicates)
Total versions: 161
Total maintainers: 1

proxy.golang.org: github.com/sertit/eoreader

Documentation: https://pkg.go.dev/github.com/sertit/eoreader#section-documentation
License: apache-2.0
Latest release: v0.22.4
published 8 months ago

Versions: 36
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent packages count: 5.5%

Average: 5.6%

Dependent repos count: 5.8%

Last synced: 6 months ago

pypi.org: eoreader

Remote-sensing opensource python library reading optical and SAR constellations, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.

Documentation: https://eoreader.readthedocs.io/latest/
License: Apache 2.0
Latest release: 0.22.4
published 8 months ago

Versions: 83
Dependent Packages: 3
Dependent Repositories: 3
Downloads: 4,742 Last month

Rankings

Dependent packages count: 3.1%

Stargazers count: 4.4%

Average: 6.6%

Downloads: 7.6%

Forks count: 8.7%

Dependent repos count: 9.0%

Maintainers (1)

rbraun

Last synced: 6 months ago

conda-forge.org: eoreader

Remote-sensing opensource python library reading optical and SAR sensors, loading and stacking bands, clouds, DEM and index.

Homepage: http://github.com/sertit/eoreader/
License: Apache-2.0
Latest release: 0.17.0
published over 3 years ago

Versions: 42
Dependent Packages: 0
Dependent Repositories: 1

Rankings

Dependent repos count: 24.3%

Stargazers count: 27.6%

Average: 36.3%

Forks count: 41.8%

Dependent packages count: 51.6%

Last synced: 6 months ago

Dependencies

requirements-doc.txt pypi

cartopy ==0.19.0
eodag *
folium *
jupyter *
linkify-it-py *
myst-nb *
myst-parser *
pystac *
sphinx *
sphinx-book-theme *
sphinx-copybutton *

requirements.txt pypi

black *
cloudpathlib >=0.7.0
colorlog *
coverage *
dask ==2021.10.0
flake8 *
geopandas >=0.9.0
h5netcdf *
lxml *
matplotlib *
methodtools *
pre-commit *
pylint *
pystac *
pytest *
pytest-cov *
rasterio >=1.2.2
rioxarray >=0.4.0
rtree *
scipy *
sertit >=1.14.0
tempenv *
tox *
tqdm *
twine *
validators *
xarray >=0.18.0

.github/workflows/publish.yml actions

actions/checkout v3 composite
actions/setup-python v4 composite
pypa/gh-action-pypi-publish release/v1 composite

.github/workflows/test.yml actions

SvanBoxel/gitlab-mirror-and-ci-action master composite
actions/checkout v3 composite

environment.yml conda

pip
python 3.9.*

pyproject.toml pypi

cloudpathlib [s3]>=0.12.1
dicttoxml *
geopandas >=0.14.4
h5netcdf *
lxml *
methodtools *
odc-geo >=0.4.6
pyresample *
rasterio >=1.3.10
rioxarray >=0.10.0
rtree *
scipy *
sertit [full]>=1.44.1
spyndex >=0.3.0
validators *
xarray >=2024.06.0
zarr *