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DOCS: Updated all docs
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davemlz authored Jan 16, 2024
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4 changes: 2 additions & 2 deletions README.md
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<a href="https://github.com/davemlz/cubo"><img src="https://github.com/davemlz/cubo/raw/main/docs/_static/logo.png" alt="cubo"></a>
</p>
<p align="center">
<em>Easily create EO mini cubes from STAC in Python</em>
<em>On-demand Earth System Data Cubes (ESDCs) from STAC in Python</em>
</p>
<p align="center">
<a href='https://pypi.python.org/pypi/cubo'>
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geospatial information. Multiple platforms are using this standard to provide clients several datasets.
Nice platforms such as [Planetary Computer](https://planetarycomputer.microsoft.com/) use this standard.

`cubo` is a Python package that provides users of STAC objects an easy way to create Earth Observation (EO) mini cubes. This is perfectly suitable for Machine Learning (ML) / Deep Learning (DL) tasks. You can easily create a lot of mini cubes by just knowing a pair of coordinates and the edge size of the cube in pixels!
`cubo` is a Python package that provides users of STAC objects an easy way to create On-demand Earth System Data Cubes (ESDCs). This is perfectly suitable for Machine Learning (ML) / Deep Learning (DL) tasks. You can easily create a lot of ESDCs by just knowing a pair of coordinates and the edge size of the cube in pixels!

Check the simple usage of `cubo` here:

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6 changes: 3 additions & 3 deletions docs/index.rst
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<a href="https://github.com/davemlz/cubo"><img src="https://github.com/davemlz/cubo/raw/main/docs/_static/logo.png" alt="cubo"></a>
</p>
<p align="center">
<em>Easily create EO mini cubes from STAC in Python</em>
<em>On-demand Earth System Data Cubes (ESDCs) from STAC in Python</em>
</p>
<p align="center">
<a href='https://pypi.python.org/pypi/cubo'>
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several datasets. Nice platforms such as Planetary Computer use this standard.

`cubo` is a Python package that provides users of STAC objects an easy way to create
Earth Observation (EO) mini cubes. This is perfectly suitable for Machine Learning (ML) /
Deep Learning (DL) tasks. You can easily create a lot of mini cubes by just knowing a pair
On-demand Earth System Data Cubes (ESDCs). This is perfectly suitable for Machine Learning (ML) /
Deep Learning (DL) tasks. You can easily create a lot of ESDCs by just knowing a pair
of coordinates and the edge size of the cube in pixels!

Check the simple usage of `cubo` here:
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6 changes: 3 additions & 3 deletions docs/tutorials/getting_started.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"Create a mini cube with an edge size of 32 pixels and a resolution of 10 m from the Sentinel-2 L2A Collection of Planetary Computer given a pair of coordinates and start and end dates using just the RGB bands:"
"Create a cube with an edge size of 32 pixels and a resolution of 10 m from the Sentinel-2 L2A Collection of Planetary Computer given a pair of coordinates and start and end dates using just the RGB bands:"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"Create a mini cube with an edge size of 128 pixels and a resolution of 20 m from the Sentinel-2 L2A Collection of Element84 given a pair of coordinates and start and end dates using just the Red Edge bands:"
"Create a cube with an edge size of 128 pixels and a resolution of 20 m from the Sentinel-2 L2A Collection of Element84 given a pair of coordinates and start and end dates using just the Red Edge bands:"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"Create a mini cube with an edge size of 64 pixels and a resolution of 10 m from the Sentinel-2 L2A Collection of Planetary Computer given a pair of coordinates and start and end dates using just the RGB bands. Additionally filter the STAC search by cloud cover values lower than 10 percent:"
"Create a cube with an edge size of 64 pixels and a resolution of 10 m from the Sentinel-2 L2A Collection of Planetary Computer given a pair of coordinates and start and end dates using just the RGB bands. Additionally filter the STAC search by cloud cover values lower than 10 percent:"
]
},
{
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