path: root/python-eoreader.spec

%global _empty_manifest_terminate_build 0
Name:		python-eoreader
Version:	0.20.0
Release:	1
Summary:	Remote-sensing opensource python library reading optical and SAR constellations, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.
License:	Apache Software License
URL:		https://pypi.org/project/eoreader/
Source0:	https://mirrors.aliyun.com/pypi/web/packages/bf/1f/9839f4df5953b5600e66b73b86c1355320f45b38b093b5a11854187b7569/eoreader-0.20.0.tar.gz
BuildArch:	noarch

Requires:	python3-lxml
Requires:	python3-h5netcdf
Requires:	python3-scipy
Requires:	python3-rasterio
Requires:	python3-xarray
Requires:	python3-rioxarray
Requires:	python3-geopandas
Requires:	python3-sertit[full]
Requires:	python3-spyndex
Requires:	python3-pyresample
Requires:	python3-zarr
Requires:	python3-rtree
Requires:	python3-validators
Requires:	python3-methodtools
Requires:	python3-dicttoxml

%description
[![pypi](https://img.shields.io/pypi/v/eoreader.svg)](https://pypi.python.org/pypi/eoreader)
[![Conda](https://img.shields.io/conda/vn/conda-forge/eoreader.svg)](https://anaconda.org/conda-forge/eoreader)
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[![Gitter](https://badges.gitter.im/eoreader/community.svg)](https://gitter.im/eoreader/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
[![Apache](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/sertit/eoreader/blob/master/LICENSE)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5082050.svg)](https://doi.org/10.5281/zenodo.5082050)
[![stars](https://img.shields.io/github/stars/sertit/eoreader?style=social)](https://github.com/sertit/eoreader)
[![Conda](https://img.shields.io/conda/dn/conda-forge/eoreader.svg)](https://anaconda.org/conda-forge/eoreader)
[![Twitter](https://img.shields.io/twitter/url/https/twitter.com/eoreader.svg?style=social&label=EOReader)](https://twitter.com/eoreader)

# ![eoreader_logo](https://eoreader.readthedocs.io/en/latest/_static/favicon.png) EOReader

**EOReader** is a remote-sensing opensource python library reading [optical](https://eoreader.readthedocs.io/en/latest/optical.html)
and [SAR](https://eoreader.readthedocs.io/en/latest/sar.html) constellations, loading and stacking bands,
clouds, DEM and spectral indices in a sensor-agnostic way.

## Managed optical constellations

[![Sentinel-2 SAFE and Theia Sentinel-3 OLCI and SLSTR Landsat 1 to 9 Harmonized Landsat-Sentinel PlanetScope, SkySat and RapidEye Pleiades and Pleiades-Neo SPOT-6/7 and 4/5 Vision-1 Maxar (WorldViews, GeoEye) SuperView-1 GEOSAT-2](https://zupimages.net/up/23/22/j3mz.png)](https://eoreader.readthedocs.io/en/latest/optical.html)

## Managed SAR constellations

[![Sentinel-1 COSMO-Skymed 1st and 2nd Generation TerraSAR-X, TanDEM-X and PAZ SAR RADARSAT-2 and RADARSAT-Constellation ICEYE SAOCOM Capella](https://zupimages.net/up/23/22/7b6k.png)](https://eoreader.readthedocs.io/en/latest/sar.html)

##  Features

EOReader implements **sensor-agnostic** features:

- [`load`](https://eoreader.readthedocs.io/en/latest/api/eoreader.products.product.Product.html#eoreader.products.product.Product.load): Load many band types:
    - satellite bands ([optical](https://eoreader.readthedocs.io/en/latest/optical.html#satellite-bands) or [SAR](https://eoreader.readthedocs.io/en/latest/sar.html#sar-bands))
    - [index](https://eoreader.readthedocs.io/en/latest/optical.html#available-index)
    - [cloud bands](https://eoreader.readthedocs.io/en/latest/optical.html#cloud-bands)
    - [DEM bands](https://eoreader.readthedocs.io/en/latest/optical.html#dem-bands)
- [`stack`](https://eoreader.readthedocs.io/en/latest/api/eoreader.products.product.Product.html#eoreader.products.product.Product.stack): Stack all these type of bands

EOReader works mainly with:
- [`xarrays.DataArray`](http://xarray.pydata.org/en/stable/generated/xarray.DataArray.html#xarray.DataArray) and [`xarrays.Dataset`](http://xarray.pydata.org/en/stable/generated/xarray.Dataset.html#xarray.Dataset) for raster data
- [`geopandas.GeoDataFrames`](https://geopandas.org/docs/user_guide/data_structures.html#geodataframe) for vector data (extents, footprints...)

## Python Quickstart

### Optical

```python
from eoreader.reader import Reader
from eoreader.bands import *

# Sentinel-2 path
s2_path = "S2B_MSIL1C_20181126T022319_N0207_R103_T51PWM_20181126T050025.SAFE"

# Create the reader object and open satellite data
reader = Reader()

# The reader will recognize the constellation from its product structure
s2_prod = reader.open(s2_path)

# Load some bands and index
bands = s2_prod.load([NDVI, GREEN, CLOUDS])

# Create a stack with some bands
stack = s2_prod.stack([RED, GREEN, BLUE], stack_path="s2_rgb_stack.tif")
```

### SAR

```python
from eoreader.reader import Reader
from eoreader.bands import *

# Sentinel-1 GRD path
s1_path = "S1B_EW_GRDM_1SDH_20200422T080459_20200422T080559_021254_028559_784D.zip"

# Create the reader object and open satellite data
reader = Reader()

# The reader will recognize the constellation from its product structure
s1_prod = reader.open(s1_path)

# Load some bands and index
bands = s1_prod.load([VV, VH])

# Create a stack with some bands
stack = s1_prod.stack([VV_DSPK, VH_DSPK], stack_path="s1_stack.tif")
```

> ⚠️**SNAP and SAR**
>
> SAR products need [`ESA SNAP`](https://senbox.atlassian.net/wiki/spaces/SNAP/pages/70503590/Creating+a+GPF+Graph)
> 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](https://eoreader.readthedocs.io/en/latest/).

## Examples

Available notebooks provided as examples:

- [Why EOReader?](https://eoreader.readthedocs.io/en/latest/notebooks/why_eoreader.html)
- [Basic tutorial](https://eoreader.readthedocs.io/en/latest/notebooks/base.html)
- [Optical data](https://eoreader.readthedocs.io/en/latest/notebooks/optical.html)
- [SAR data](https://eoreader.readthedocs.io/en/latest/notebooks/SAR.html)
- [VHR data](https://eoreader.readthedocs.io/en/latest/notebooks/VHR.html)
- [Remove clouds](https://eoreader.readthedocs.io/en/latest/notebooks/remove_clouds.html)
- [Sentinel-3 data](https://eoreader.readthedocs.io/en/latest/notebooks/sentinel-3.html)
- [Water detection on multiple products](https://eoreader.readthedocs.io/en/latest/notebooks/water_detection.html)
- [Windowed Reading](https://eoreader.readthedocs.io/en/latest/notebooks/windowed_reading.html)
- [DEM](https://eoreader.readthedocs.io/en/latest/notebooks/dem.html)
- [Custom stacks](https://eoreader.readthedocs.io/en/latest/notebooks/custom.html)
- [Methods to clean optical bands](https://eoreader.readthedocs.io/en/latest/notebooks/optical_cleaning_methods.html)
- [S3 Compatible Storage](https://eoreader.readthedocs.io/en/latest/notebooks/s3_compatible_storage.html)
- [Dask](https://eoreader.readthedocs.io/en/latest/notebooks/dask.html)
- [STAC](https://eoreader.readthedocs.io/en/latest/notebooks/stac.html)

## Installation

### Pip

You can install EOReader via pip:

`pip install eoreader`

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

On Windows and with pip, you may face installation issues due to GDAL.
The well known workaround of installing from [Gohlke's wheels](https://www.lfd.uci.edu/~gohlke/pythonlibs/#rasterio)
also applies here.
Please look at the [rasterio page](https://rasterio.readthedocs.io/en/latest/installation.html)
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](https://emergency.copernicus.eu/) Rapid Mapping and Risk and Recovery Mapping operators, 
[SERTIT](https://sertit.unistra.fr/) 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 !

## Talks

- GeoPython 2022 [ [PDF](https://seafile.unistra.fr/f/be2b461af970465b903e/) ] [ [YouTube](https://www.youtube.com/watch?v=mKxOiRULOJA&t=14303s) ]
- Mentionned in **[Live+]SIG 2022 by ESRI France** (in French):
  `Enrichir ArcgisPro grâce à des processus personnalisés d'observation de la Terre`
  [ [PDF](https://seafile.unistra.fr/f/9502a14f142041468837/) ]
- 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`](https://doi.org/10.5194/egusphere-egu23-14143) 

## Press Release

- [ESA Success Story](https://earth.esa.int/eogateway/news/new-open-source-python-library-improves-rapid-mapping-services)

## 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)](https://doi.org/10.3390/rs14205253)

## License

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

## Authors

**EOReader** has been created by [ICube-SERTIT](https://sertit.unistra.fr/).
Follow us on [Twitter](https://twitter.com/eoreader).

## Credits

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

- [`geopandas`](https://geopandas.org/)
- [`rasterio`](https://rasterio.readthedocs.io/en/latest/)
- [`xarray`](http://xarray.pydata.org/en/stable/)
- [`rioxarray`](https://corteva.github.io/rioxarray/stable/)
- [`awesome-spectral-indices` and `spyndex`](https://awesome-ee-spectral-indices.readthedocs.io/en/latest/index.html)




%package -n python3-eoreader
Summary:	Remote-sensing opensource python library reading optical and SAR constellations, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.
Provides:	python-eoreader
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-eoreader
[![pypi](https://img.shields.io/pypi/v/eoreader.svg)](https://pypi.python.org/pypi/eoreader)
[![Conda](https://img.shields.io/conda/vn/conda-forge/eoreader.svg)](https://anaconda.org/conda-forge/eoreader)
[![Tests](https://github.com/sertit/eoreader/actions/workflows/test.yml/badge.svg)](https://github.com/sertit/eoreader/actions/workflows/test.yml)
[![Gitter](https://badges.gitter.im/eoreader/community.svg)](https://gitter.im/eoreader/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
[![Apache](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/sertit/eoreader/blob/master/LICENSE)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5082050.svg)](https://doi.org/10.5281/zenodo.5082050)
[![stars](https://img.shields.io/github/stars/sertit/eoreader?style=social)](https://github.com/sertit/eoreader)
[![Conda](https://img.shields.io/conda/dn/conda-forge/eoreader.svg)](https://anaconda.org/conda-forge/eoreader)
[![Twitter](https://img.shields.io/twitter/url/https/twitter.com/eoreader.svg?style=social&label=EOReader)](https://twitter.com/eoreader)

# ![eoreader_logo](https://eoreader.readthedocs.io/en/latest/_static/favicon.png) EOReader

**EOReader** is a remote-sensing opensource python library reading [optical](https://eoreader.readthedocs.io/en/latest/optical.html)
and [SAR](https://eoreader.readthedocs.io/en/latest/sar.html) constellations, loading and stacking bands,
clouds, DEM and spectral indices in a sensor-agnostic way.

## Managed optical constellations

[![Sentinel-2 SAFE and Theia Sentinel-3 OLCI and SLSTR Landsat 1 to 9 Harmonized Landsat-Sentinel PlanetScope, SkySat and RapidEye Pleiades and Pleiades-Neo SPOT-6/7 and 4/5 Vision-1 Maxar (WorldViews, GeoEye) SuperView-1 GEOSAT-2](https://zupimages.net/up/23/22/j3mz.png)](https://eoreader.readthedocs.io/en/latest/optical.html)

## Managed SAR constellations

[![Sentinel-1 COSMO-Skymed 1st and 2nd Generation TerraSAR-X, TanDEM-X and PAZ SAR RADARSAT-2 and RADARSAT-Constellation ICEYE SAOCOM Capella](https://zupimages.net/up/23/22/7b6k.png)](https://eoreader.readthedocs.io/en/latest/sar.html)

##  Features

EOReader implements **sensor-agnostic** features:

- [`load`](https://eoreader.readthedocs.io/en/latest/api/eoreader.products.product.Product.html#eoreader.products.product.Product.load): Load many band types:
    - satellite bands ([optical](https://eoreader.readthedocs.io/en/latest/optical.html#satellite-bands) or [SAR](https://eoreader.readthedocs.io/en/latest/sar.html#sar-bands))
    - [index](https://eoreader.readthedocs.io/en/latest/optical.html#available-index)
    - [cloud bands](https://eoreader.readthedocs.io/en/latest/optical.html#cloud-bands)
    - [DEM bands](https://eoreader.readthedocs.io/en/latest/optical.html#dem-bands)
- [`stack`](https://eoreader.readthedocs.io/en/latest/api/eoreader.products.product.Product.html#eoreader.products.product.Product.stack): Stack all these type of bands

EOReader works mainly with:
- [`xarrays.DataArray`](http://xarray.pydata.org/en/stable/generated/xarray.DataArray.html#xarray.DataArray) and [`xarrays.Dataset`](http://xarray.pydata.org/en/stable/generated/xarray.Dataset.html#xarray.Dataset) for raster data
- [`geopandas.GeoDataFrames`](https://geopandas.org/docs/user_guide/data_structures.html#geodataframe) for vector data (extents, footprints...)

## Python Quickstart

### Optical

```python
from eoreader.reader import Reader
from eoreader.bands import *

# Sentinel-2 path
s2_path = "S2B_MSIL1C_20181126T022319_N0207_R103_T51PWM_20181126T050025.SAFE"

# Create the reader object and open satellite data
reader = Reader()

# The reader will recognize the constellation from its product structure
s2_prod = reader.open(s2_path)

# Load some bands and index
bands = s2_prod.load([NDVI, GREEN, CLOUDS])

# Create a stack with some bands
stack = s2_prod.stack([RED, GREEN, BLUE], stack_path="s2_rgb_stack.tif")
```

### SAR

```python
from eoreader.reader import Reader
from eoreader.bands import *

# Sentinel-1 GRD path
s1_path = "S1B_EW_GRDM_1SDH_20200422T080459_20200422T080559_021254_028559_784D.zip"

# Create the reader object and open satellite data
reader = Reader()

# The reader will recognize the constellation from its product structure
s1_prod = reader.open(s1_path)

# Load some bands and index
bands = s1_prod.load([VV, VH])

# Create a stack with some bands
stack = s1_prod.stack([VV_DSPK, VH_DSPK], stack_path="s1_stack.tif")
```

> ⚠️**SNAP and SAR**
>
> SAR products need [`ESA SNAP`](https://senbox.atlassian.net/wiki/spaces/SNAP/pages/70503590/Creating+a+GPF+Graph)
> 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](https://eoreader.readthedocs.io/en/latest/).

## Examples

Available notebooks provided as examples:

- [Why EOReader?](https://eoreader.readthedocs.io/en/latest/notebooks/why_eoreader.html)
- [Basic tutorial](https://eoreader.readthedocs.io/en/latest/notebooks/base.html)
- [Optical data](https://eoreader.readthedocs.io/en/latest/notebooks/optical.html)
- [SAR data](https://eoreader.readthedocs.io/en/latest/notebooks/SAR.html)
- [VHR data](https://eoreader.readthedocs.io/en/latest/notebooks/VHR.html)
- [Remove clouds](https://eoreader.readthedocs.io/en/latest/notebooks/remove_clouds.html)
- [Sentinel-3 data](https://eoreader.readthedocs.io/en/latest/notebooks/sentinel-3.html)
- [Water detection on multiple products](https://eoreader.readthedocs.io/en/latest/notebooks/water_detection.html)
- [Windowed Reading](https://eoreader.readthedocs.io/en/latest/notebooks/windowed_reading.html)
- [DEM](https://eoreader.readthedocs.io/en/latest/notebooks/dem.html)
- [Custom stacks](https://eoreader.readthedocs.io/en/latest/notebooks/custom.html)
- [Methods to clean optical bands](https://eoreader.readthedocs.io/en/latest/notebooks/optical_cleaning_methods.html)
- [S3 Compatible Storage](https://eoreader.readthedocs.io/en/latest/notebooks/s3_compatible_storage.html)
- [Dask](https://eoreader.readthedocs.io/en/latest/notebooks/dask.html)
- [STAC](https://eoreader.readthedocs.io/en/latest/notebooks/stac.html)

## Installation

### Pip

You can install EOReader via pip:

`pip install eoreader`

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

On Windows and with pip, you may face installation issues due to GDAL.
The well known workaround of installing from [Gohlke's wheels](https://www.lfd.uci.edu/~gohlke/pythonlibs/#rasterio)
also applies here.
Please look at the [rasterio page](https://rasterio.readthedocs.io/en/latest/installation.html)
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](https://emergency.copernicus.eu/) Rapid Mapping and Risk and Recovery Mapping operators, 
[SERTIT](https://sertit.unistra.fr/) 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 !

## Talks

- GeoPython 2022 [ [PDF](https://seafile.unistra.fr/f/be2b461af970465b903e/) ] [ [YouTube](https://www.youtube.com/watch?v=mKxOiRULOJA&t=14303s) ]
- Mentionned in **[Live+]SIG 2022 by ESRI France** (in French):
  `Enrichir ArcgisPro grâce à des processus personnalisés d'observation de la Terre`
  [ [PDF](https://seafile.unistra.fr/f/9502a14f142041468837/) ]
- 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`](https://doi.org/10.5194/egusphere-egu23-14143) 

## Press Release

- [ESA Success Story](https://earth.esa.int/eogateway/news/new-open-source-python-library-improves-rapid-mapping-services)

## 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)](https://doi.org/10.3390/rs14205253)

## License

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

## Authors

**EOReader** has been created by [ICube-SERTIT](https://sertit.unistra.fr/).
Follow us on [Twitter](https://twitter.com/eoreader).

## Credits

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

- [`geopandas`](https://geopandas.org/)
- [`rasterio`](https://rasterio.readthedocs.io/en/latest/)
- [`xarray`](http://xarray.pydata.org/en/stable/)
- [`rioxarray`](https://corteva.github.io/rioxarray/stable/)
- [`awesome-spectral-indices` and `spyndex`](https://awesome-ee-spectral-indices.readthedocs.io/en/latest/index.html)




%package help
Summary:	Development documents and examples for eoreader
Provides:	python3-eoreader-doc
%description help
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# ![eoreader_logo](https://eoreader.readthedocs.io/en/latest/_static/favicon.png) EOReader

**EOReader** is a remote-sensing opensource python library reading [optical](https://eoreader.readthedocs.io/en/latest/optical.html)
and [SAR](https://eoreader.readthedocs.io/en/latest/sar.html) constellations, loading and stacking bands,
clouds, DEM and spectral indices in a sensor-agnostic way.

## Managed optical constellations

[![Sentinel-2 SAFE and Theia Sentinel-3 OLCI and SLSTR Landsat 1 to 9 Harmonized Landsat-Sentinel PlanetScope, SkySat and RapidEye Pleiades and Pleiades-Neo SPOT-6/7 and 4/5 Vision-1 Maxar (WorldViews, GeoEye) SuperView-1 GEOSAT-2](https://zupimages.net/up/23/22/j3mz.png)](https://eoreader.readthedocs.io/en/latest/optical.html)

## Managed SAR constellations

[![Sentinel-1 COSMO-Skymed 1st and 2nd Generation TerraSAR-X, TanDEM-X and PAZ SAR RADARSAT-2 and RADARSAT-Constellation ICEYE SAOCOM Capella](https://zupimages.net/up/23/22/7b6k.png)](https://eoreader.readthedocs.io/en/latest/sar.html)

##  Features

EOReader implements **sensor-agnostic** features:

- [`load`](https://eoreader.readthedocs.io/en/latest/api/eoreader.products.product.Product.html#eoreader.products.product.Product.load): Load many band types:
    - satellite bands ([optical](https://eoreader.readthedocs.io/en/latest/optical.html#satellite-bands) or [SAR](https://eoreader.readthedocs.io/en/latest/sar.html#sar-bands))
    - [index](https://eoreader.readthedocs.io/en/latest/optical.html#available-index)
    - [cloud bands](https://eoreader.readthedocs.io/en/latest/optical.html#cloud-bands)
    - [DEM bands](https://eoreader.readthedocs.io/en/latest/optical.html#dem-bands)
- [`stack`](https://eoreader.readthedocs.io/en/latest/api/eoreader.products.product.Product.html#eoreader.products.product.Product.stack): Stack all these type of bands

EOReader works mainly with:
- [`xarrays.DataArray`](http://xarray.pydata.org/en/stable/generated/xarray.DataArray.html#xarray.DataArray) and [`xarrays.Dataset`](http://xarray.pydata.org/en/stable/generated/xarray.Dataset.html#xarray.Dataset) for raster data
- [`geopandas.GeoDataFrames`](https://geopandas.org/docs/user_guide/data_structures.html#geodataframe) for vector data (extents, footprints...)

## Python Quickstart

### Optical

```python
from eoreader.reader import Reader
from eoreader.bands import *

# Sentinel-2 path
s2_path = "S2B_MSIL1C_20181126T022319_N0207_R103_T51PWM_20181126T050025.SAFE"

# Create the reader object and open satellite data
reader = Reader()

# The reader will recognize the constellation from its product structure
s2_prod = reader.open(s2_path)

# Load some bands and index
bands = s2_prod.load([NDVI, GREEN, CLOUDS])

# Create a stack with some bands
stack = s2_prod.stack([RED, GREEN, BLUE], stack_path="s2_rgb_stack.tif")
```

### SAR

```python
from eoreader.reader import Reader
from eoreader.bands import *

# Sentinel-1 GRD path
s1_path = "S1B_EW_GRDM_1SDH_20200422T080459_20200422T080559_021254_028559_784D.zip"

# Create the reader object and open satellite data
reader = Reader()

# The reader will recognize the constellation from its product structure
s1_prod = reader.open(s1_path)

# Load some bands and index
bands = s1_prod.load([VV, VH])

# Create a stack with some bands
stack = s1_prod.stack([VV_DSPK, VH_DSPK], stack_path="s1_stack.tif")
```

> ⚠️**SNAP and SAR**
>
> SAR products need [`ESA SNAP`](https://senbox.atlassian.net/wiki/spaces/SNAP/pages/70503590/Creating+a+GPF+Graph)
> 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](https://eoreader.readthedocs.io/en/latest/).

## Examples

Available notebooks provided as examples:

- [Why EOReader?](https://eoreader.readthedocs.io/en/latest/notebooks/why_eoreader.html)
- [Basic tutorial](https://eoreader.readthedocs.io/en/latest/notebooks/base.html)
- [Optical data](https://eoreader.readthedocs.io/en/latest/notebooks/optical.html)
- [SAR data](https://eoreader.readthedocs.io/en/latest/notebooks/SAR.html)
- [VHR data](https://eoreader.readthedocs.io/en/latest/notebooks/VHR.html)
- [Remove clouds](https://eoreader.readthedocs.io/en/latest/notebooks/remove_clouds.html)
- [Sentinel-3 data](https://eoreader.readthedocs.io/en/latest/notebooks/sentinel-3.html)
- [Water detection on multiple products](https://eoreader.readthedocs.io/en/latest/notebooks/water_detection.html)
- [Windowed Reading](https://eoreader.readthedocs.io/en/latest/notebooks/windowed_reading.html)
- [DEM](https://eoreader.readthedocs.io/en/latest/notebooks/dem.html)
- [Custom stacks](https://eoreader.readthedocs.io/en/latest/notebooks/custom.html)
- [Methods to clean optical bands](https://eoreader.readthedocs.io/en/latest/notebooks/optical_cleaning_methods.html)
- [S3 Compatible Storage](https://eoreader.readthedocs.io/en/latest/notebooks/s3_compatible_storage.html)
- [Dask](https://eoreader.readthedocs.io/en/latest/notebooks/dask.html)
- [STAC](https://eoreader.readthedocs.io/en/latest/notebooks/stac.html)

## Installation

### Pip

You can install EOReader via pip:

`pip install eoreader`

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

On Windows and with pip, you may face installation issues due to GDAL.
The well known workaround of installing from [Gohlke's wheels](https://www.lfd.uci.edu/~gohlke/pythonlibs/#rasterio)
also applies here.
Please look at the [rasterio page](https://rasterio.readthedocs.io/en/latest/installation.html)
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](https://emergency.copernicus.eu/) Rapid Mapping and Risk and Recovery Mapping operators, 
[SERTIT](https://sertit.unistra.fr/) 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 !

## Talks

- GeoPython 2022 [ [PDF](https://seafile.unistra.fr/f/be2b461af970465b903e/) ] [ [YouTube](https://www.youtube.com/watch?v=mKxOiRULOJA&t=14303s) ]
- Mentionned in **[Live+]SIG 2022 by ESRI France** (in French):
  `Enrichir ArcgisPro grâce à des processus personnalisés d'observation de la Terre`
  [ [PDF](https://seafile.unistra.fr/f/9502a14f142041468837/) ]
- 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`](https://doi.org/10.5194/egusphere-egu23-14143) 

## Press Release

- [ESA Success Story](https://earth.esa.int/eogateway/news/new-open-source-python-library-improves-rapid-mapping-services)

## 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)](https://doi.org/10.3390/rs14205253)

## License

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

## Authors

**EOReader** has been created by [ICube-SERTIT](https://sertit.unistra.fr/).
Follow us on [Twitter](https://twitter.com/eoreader).

## Credits

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

- [`geopandas`](https://geopandas.org/)
- [`rasterio`](https://rasterio.readthedocs.io/en/latest/)
- [`xarray`](http://xarray.pydata.org/en/stable/)
- [`rioxarray`](https://corteva.github.io/rioxarray/stable/)
- [`awesome-spectral-indices` and `spyndex`](https://awesome-ee-spectral-indices.readthedocs.io/en/latest/index.html)




%prep
%autosetup -n eoreader-0.20.0

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-eoreader -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 0.20.0-1
- Package Spec generated