From f6dd6cea8b197f904a87dfa69f346b96bb0d8750 Mon Sep 17 00:00:00 2001
From: David Montero Loaiza <49817852+davemlz@users.noreply.github.com>
Date: Tue, 16 Jan 2024 12:51:02 +0100
Subject: [PATCH] DOCS: Updated all docs
---
README.md | 4 ++--
docs/index.rst | 6 +++---
docs/tutorials/getting_started.ipynb | 6 +++---
3 files changed, 8 insertions(+), 8 deletions(-)
diff --git a/README.md b/README.md
index 87d038e..0caa742 100644
--- a/README.md
+++ b/README.md
@@ -2,7 +2,7 @@
- Easily create EO mini cubes from STAC in Python
+ On-demand Earth System Data Cubes (ESDCs) from STAC in Python
@@ -60,7 +60,7 @@
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:
diff --git a/docs/index.rst b/docs/index.rst
index 87aa786..2b718fd 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -15,7 +15,7 @@ Cubo
- Easily create EO mini cubes from STAC in Python
+ On-demand Earth System Data Cubes (ESDCs) from STAC in Python
@@ -61,8 +61,8 @@ geospatial information. Multiple platforms are using this standard to provide cl
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:
diff --git a/docs/tutorials/getting_started.ipynb b/docs/tutorials/getting_started.ipynb
index d2f8e88..cb879e4 100644
--- a/docs/tutorials/getting_started.ipynb
+++ b/docs/tutorials/getting_started.ipynb
@@ -30,7 +30,7 @@
"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:"
]
},
{
@@ -602,7 +602,7 @@
"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:"
]
},
{
@@ -1316,7 +1316,7 @@
"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:"
]
},
{