diff --git a/README.md b/README.md
index 0caa742..01361ea 100644
--- a/README.md
+++ b/README.md
@@ -2,7 +2,7 @@
   <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>On-demand Earth System Data Cubes (ESDCs) from STAC in Python</em>
+    <em>On-Demand Earth System Data Cubes (ESDCs) in Python</em>
 </p>
 <p align="center">
 <a href='https://pypi.python.org/pypi/cubo'>
@@ -59,10 +59,12 @@
 [SpatioTemporal Asset Catalogs (STAC)](https://stacspec.org/) provide a standardized format that describes
 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.
+Additionally, [Google Earth Engine (GEE)](https://developers.google.com/earth-engine/datasets/) 
+also provides a gigantic catalogue that users can harness for different tasks in Python.
 
-`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!
+`cubo` is a Python package that provides users of STAC and GEE an easy way to create On-Demand Earth System Data Cubes (ESDCs). This is perfectly suitable for 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:
+Check the simple usage of `cubo` with STAC here:
 
 ```python
 import cubo
@@ -84,6 +86,29 @@ da = cubo.create(
 
 This chunk of code just created an `xr.DataArray` object given a pair of coordinates, the edge size of the cube (in pixels), and additional information to get the data from STAC (Planetary Computer by default, but you can use another provider!). Note that you can also use the resolution you want (in meters) and the bands that you require.
 
+Now check the simple usage of `cubo` with GEE here:
+
+```python
+import cubo
+import xarray as xr
+
+da = cubo.create(
+    lat=51.079225, # Central latitude of the cube
+    lon=10.452173, # Central longitude of the cube
+    collection="COPERNICUS/S2_SR_HARMONIZED", # Id of the GEE collection
+    bands=["B2","B3","B4"], # Bands to retrieve
+    start_date="2016-06-01", # Start date of the cube
+    end_date="2017-07-01", # End date of the cube
+    edge_size=128, # Edge size of the cube (px)
+    resolution=10, # Pixel size of the cube (m)
+    gee=True # Use GEE instead of STAC
+)
+```
+
+This chunk of code is very similar to the STAC-based cubo code. Note that the `collection`
+is now the ID of the GEE collection to use, and note that the `gee` argument must be set to
+`True`.
+
 ## How does it work?
 
 The thing is super easy and simple.
@@ -91,8 +116,9 @@ The thing is super easy and simple.
 1. You have the coordinates of a point of interest. The cube will be created around these coordinates (i.e., these coordinates will be approximately the spatial center of the cube).
 2. Internally, the coordinates are transformed to the projected UTM coordinates [x,y] in meters (i.e., local UTM CRS). They are rounded to the closest pair of coordinates that are divisible by the resolution you requested.
 3. The edge size you provide is used to create a Bounding Box (BBox) for the cube in the local UTM CRS given the exact amount of pixels (Note that the edge size should be a multiple of 2, otherwise it will be rounded, usual edge sizes for ML are 64, 128, 256, 512, etc.).
-4. Additional information is used to retrieve the data from the STAC catalogue: starts and end dates, name of the collection, endpoint of the catalogue, etc.
-5. Then, by using `stackstac` and `pystac_client` the mini cube is retrieved as a `xr. DataArray`.
+4. Additional information is used to retrieve the data from the STAC catalogue or from GEE: starts and end dates, name of the collection, endpoint of the catalogue (ignored for GEE), etc.
+5. Then, by using `stackstac` and `pystac_client` the cube is retrieved as a `xr. DataArray`. In the case of GEE, the cube is retrieved
+via `xee`.
 6. Success! That's what `cubo` is doing for you, and you just need to provide the coordinates, the edge size, and the additional info to get the cube.
 
 ## Installation
@@ -103,6 +129,12 @@ Install the latest version from PyPI:
 pip install cubo
 ```
 
+Install `cubo` with the required GEE dependencies from PyPI:
+
+```
+pip install cubo[ee]
+```
+
 Upgrade `cubo` by running:
 
 ```
diff --git a/cubo/cubo.py b/cubo/cubo.py
index 6849d5e..f75e4c4 100644
--- a/cubo/cubo.py
+++ b/cubo/cubo.py
@@ -21,6 +21,7 @@ def create(
     edge_size: Union[float, int] = 128.0,
     resolution: Union[float, int] = 10.0,
     stac: str = "https://planetarycomputer.microsoft.com/api/stac/v1",
+    gee: bool = False,
     **kwargs,
 ) -> xr.DataArray:
     """Creates a data cube from a STAC Catalogue as a :code:`xr.DataArray` object.
@@ -52,6 +53,11 @@ def create(
         Pixel size in meters.
     stac : str, default = 'https://planetarycomputer.microsoft.com/api/stac/v1'
         Endpoint of the STAC Catalogue to use.
+    gee : bool, default = True
+        Whether to use Google Earth Engine. This ignores the 'stac' argument.
+
+        .. versionadded:: 2024.1.0
+
     kwargs :
         Additional keyword arguments passed to :code:`pystac_client.Client.search()`.
 
@@ -77,51 +83,127 @@ def create(
     ...     resolution=10,
     ... )
     <xarray.DataArray (time: 3, band: 3, x: 32, y: 32)>
+
+    Create a Sentinel-2 L2A data cube with an edge size of 128 px from Google Earth Engine:
+
+    >>> import cubo
+    >>> cubo.create(
+    ...     lat=51.079225,
+    ...     lon=10.452173,
+    ...     collection="COPERNICUS/S2_SR_HARMONIZED",
+    ...     bands=["B2","B3","B4"],
+    ...     start_date="2016-06-01",
+    ...     end_date="2017-07-01",
+    ...     edge_size=128,
+    ...     resolution=10,
+    ...     gee=True,
+    ... )
+    <xarray.DataArray (time: 27, band: 3, x: 128, y: 128)>
     """
     # Get the BBox and EPSG
     bbox_utm, bbox_latlon, utm_coords, epsg = _central_pixel_bbox(
         lat, lon, edge_size, resolution
     )
 
-    # Convert UTM Bbox to a Feature
-    bbox_utm = rasterio.features.bounds(bbox_utm)
-
-    # Open the Catalogue
-    CATALOG = pystac_client.Client.open(stac)
-
-    # Do a search
-    SEARCH = CATALOG.search(
-        intersects=bbox_latlon,
-        datetime=f"{start_date}/{end_date}",
-        collections=[collection],
-        **kwargs,
-    )
-
-    # Get all items and sign if using Planetary Computer
-    items = SEARCH.item_collection()
-
-    if stac == "https://planetarycomputer.microsoft.com/api/stac/v1":
-        items = pc.sign(items)
-
-    # Put the bands into list if not a list already
-    if not isinstance(bands, list) and bands is not None:
-        bands = [bands]
-
-    # Create the cube
-    cube = stackstac.stack(
-        items,
-        assets=bands,
-        resolution=resolution,
-        bounds=bbox_utm,
-        epsg=epsg,
-    )
-
-    # Delete attributes
-    attributes = ["spec", "crs", "transform", "resolution"]
-
-    for attribute in attributes:
-        if attribute in cube.attrs:
-            del cube.attrs[attribute]
+    # Use Google Earth Engine
+    if gee:
+        
+        # Try to import ee, otherwise raise an ImportError
+        try:
+            import xee
+            import ee
+        except ImportError:
+            raise ImportError(
+                    '"earthengine-api" and "xee" could not be loaded. Please install them, or install "cubo" using "pip install cubo[ee]"'
+                )
+
+        # Initialize Google Earth Engine with the high volume endpoint
+        ee.Initialize(opt_url='https://earthengine-highvolume.googleapis.com')
+
+        # Get BBox values in latlon
+        west = bbox_latlon['coordinates'][0][0][0]
+        south = bbox_latlon['coordinates'][0][0][1]
+        east = bbox_latlon['coordinates'][0][2][0]
+        north = bbox_latlon['coordinates'][0][2][1]
+
+        # Create the BBox geometry in GEE
+        BBox = ee.Geometry.BBox(west,south,east,north)
+
+        # If the collection is string then access the Image Collection
+        if isinstance(collection,str):
+            collection = ee.ImageCollection(collection)
+
+        # Do the filtering: Bounds, time, and bands
+        collection = (
+            collection
+                .filterBounds(BBox)
+                .filterDate(start_date,end_date)
+                .select(bands)
+        )
+
+        # Return the cube via xee
+        cube = xr.open_dataset(
+            collection,
+            engine="ee",
+            geometry=BBox,
+            scale=resolution,
+            crs=f"EPSG:{epsg}",
+            chunks=dict()
+        )
+
+        # Rename the coords to match stackstac names, also rearrange
+        cube = cube.rename(Y="y",X="x").to_array("band").transpose("time","band","y","x")
+
+        # Delete all attributes
+        cube.attrs = dict()
+
+        # Get the name of the collection
+        collection = collection.get('system:id').getInfo()
+
+        # Override the stac argument using the GEE STAC
+        stac = "https://earthengine-stac.storage.googleapis.com/catalog/catalog.json"
+
+    else:
+
+        # Convert UTM Bbox to a Feature
+        bbox_utm = rasterio.features.bounds(bbox_utm)
+
+        # Open the Catalogue
+        CATALOG = pystac_client.Client.open(stac)
+
+        # Do a search
+        SEARCH = CATALOG.search(
+            intersects=bbox_latlon,
+            datetime=f"{start_date}/{end_date}",
+            collections=[collection],
+            **kwargs,
+        )
+
+        # Get all items and sign if using Planetary Computer
+        items = SEARCH.item_collection()
+
+        if stac == "https://planetarycomputer.microsoft.com/api/stac/v1":
+            items = pc.sign(items)
+
+        # Put the bands into list if not a list already
+        if not isinstance(bands, list) and bands is not None:
+            bands = [bands]
+
+        # Create the cube
+        cube = stackstac.stack(
+            items,
+            assets=bands,
+            resolution=resolution,
+            bounds=bbox_utm,
+            epsg=epsg,
+        )
+
+        # Delete attributes
+        attributes = ["spec", "crs", "transform", "resolution"]
+
+        for attribute in attributes:
+            if attribute in cube.attrs:
+                del cube.attrs[attribute]
 
     # New attributes
     cube.attrs = dict(
diff --git a/docs/changelog.rst b/docs/changelog.rst
index 8bfa137..cf13f37 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -1,6 +1,17 @@
 Changelog
 =========
 
+v2024.1.0
+---------
+
+- Added support for Google Earth Engine.
+- Added the :code:`gee` argument to :code:`cubo.create()`.
+
+v2023.12.0
+---------
+
+- Added preservation via Zenodo.
+
 v2023.7.2
 ---------
 
diff --git a/docs/index.rst b/docs/index.rst
index 2b718fd..4a2e203 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -15,7 +15,7 @@ Cubo
    <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>On-demand Earth System Data Cubes (ESDCs) from STAC in Python</em>
+      <em>On-Demand Earth System Data Cubes (ESDCs) in Python</em>
    </p>
    <p align="center">
    <a href='https://pypi.python.org/pypi/cubo'>
@@ -59,13 +59,15 @@ Overview
 SpatioTemporal Asset Catalogs (STAC) provide a standardized format that describes
 geospatial information. Multiple platforms are using this standard to provide clients 
 several datasets. Nice platforms such as Planetary Computer use this standard.
+Additionally, Google Earth Engine (GEE) also provides a gigantic catalogue that users can 
+harness for different tasks in Python.
 
-`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) / 
+`cubo` is a Python package that provides users of STAC and GEE an easy way to create 
+On-demand Earth System Data Cubes (ESDCs). This is perfectly suitable for 
 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:
+Check the simple usage of `cubo` with STAC here:
 
 .. code-block:: python
 
@@ -96,6 +98,29 @@ coordinates, the edge size of the cube (in pixels), and additional information t
 data from STAC (Planetary Computer by default, but you can use another provider!). Note 
 that you can also use the resolution you want (in meters) and the bands that you require.
 
+Now check the simple usage of `cubo` with GEE here:
+
+.. code-block:: python
+
+   import cubo
+   import xarray as xr
+
+   da = cubo.create(
+      lat=51.079225, # Central latitude of the cube
+      lon=10.452173, # Central longitude of the cube
+      collection="COPERNICUS/S2_SR_HARMONIZED", # Id of the GEE collection
+      bands=["B2","B3","B4"], # Bands to retrieve
+      start_date="2016-06-01", # Start date of the cube
+      end_date="2017-07-01", # End date of the cube
+      edge_size=128, # Edge size of the cube (px)
+      resolution=10, # Pixel size of the cube (m)
+      gee=True # Use GEE instead of STAC
+   )
+
+This chunk of code is very similar to the STAC-based cubo code. Note that the :code:`collection`
+is now the ID of the GEE collection to use, and note that the :code:`gee` argument must be set to
+:code:`True`.
+
 How does it work?
 -----------------
 
@@ -110,10 +135,10 @@ that are divisible by the resolution you requested.
 local UTM CRS given the exact amount of pixels (Note that the edge size should be a 
 multiple of 2, otherwise it will be rounded, usual edge sizes for ML are 64, 128, 256, 
 512, etc.).
-4. Additional information is used to retrieve the data from the STAC catalogue: starts 
-and end dates, name of the collection, endpoint of the catalogue, etc.
-5. Then, by using `stackstac` and `pystac_client` the mini cube is retrieved as a 
-`xr.DataArray`.
+4. Additional information is used to retrieve the data from the STAC catalogue or from GEE: starts 
+and end dates, name of the collection, endpoint of the catalogue (ignored for GEE), etc.
+5. Then, by using :code:`stackstac` and :code:`pystac_client` the cube is retrieved as a 
+:code:`xr.DataArray`. In the case of GEE, the cube is retrieved via :code:`xee`.
 6. Success! That's what `cubo` is doing for you, and you just need to provide the 
 coordinates, the edge size, and the additional info to get the cube.
 
@@ -127,6 +152,12 @@ Install the latest version from PyPI:
    pip install cubo
 
 
+Install `cubo` with the required GEE dependencies from PyPI:
+
+.. code-block::
+
+   pip install cubo[ee]
+
 Upgrade `cubo` by running:
 
 .. code-block::
diff --git a/docs/tutorials.rst b/docs/tutorials.rst
index 8de4888..54c9940 100644
--- a/docs/tutorials.rst
+++ b/docs/tutorials.rst
@@ -7,4 +7,5 @@ Tutorials
     tutorials/getting_started.ipynb
     tutorials/cube_visualization.ipynb
     tutorials/using_collections.ipynb
-    tutorials/visualization_lexcube.ipynb
\ No newline at end of file
+    tutorials/visualization_lexcube.ipynb
+    tutorials/using_gee.ipynb
\ No newline at end of file
diff --git a/docs/tutorials/using_gee.ipynb b/docs/tutorials/using_gee.ipynb
new file mode 100644
index 0000000..fcf8bb2
--- /dev/null
+++ b/docs/tutorials/using_gee.ipynb
@@ -0,0 +1,1371 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Using Google Earth Engine"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This tutorial shows how to harness data from Google Earth Engine using `cubo`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cubo\n",
+    "import ee"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Initialize the high volume endpoint from Google Earth Engine:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ee.Initialize(opt_url='https://earthengine-highvolume.googleapis.com')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "`cubo` works in a similar way for GEE, and you just have to consider the two following things:\n",
+    "\n",
+    "- Set `gee=True` inside the function.\n",
+    "- Set `collection` to the ID of the GEE collection to use, or a `ee.ImageCollection` object."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example 1: Use the ID of a GEE Collection\n",
+    "\n",
+    "Let's try first with just the ID of a collection:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
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+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
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+       ":root {\n",
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+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=dark],\n",
+       "body[data-theme=dark],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;COPERNICUS/S2_SR_HARMONIZED&#x27; (time: 12, band: 3, y: 64, x: 64)&gt;\n",
+       "dask.array&lt;transpose, shape=(12, 3, 64, 64), dtype=int32, chunksize=(12, 1, 64, 64), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "  * time                       (time) datetime64[ns] 2021-06-02T10:17:25.4740...\n",
+       "  * x                          (x) float64 3.784e+05 3.785e+05 ... 3.791e+05\n",
+       "  * y                          (y) float64 5.301e+06 5.301e+06 ... 5.3e+06\n",
+       "  * band                       (band) object &#x27;B2&#x27; &#x27;B3&#x27; &#x27;B4&#x27;\n",
+       "    cubo:distance_from_center  (y, x) float64 445.7 438.8 432.0 ... 438.3 445.4\n",
+       "Attributes:\n",
+       "    collection:           COPERNICUS/S2_SR_HARMONIZED\n",
+       "    stac:                 https://earthengine-stac.storage.googleapis.com/cat...\n",
+       "    epsg:                 32633\n",
+       "    resolution:           10\n",
+       "    edge_size:            64\n",
+       "    central_lat:          47.848151988493385\n",
+       "    central_lon:          13.379491178028564\n",
+       "    central_y:            5300694.38448788\n",
+       "    central_x:            378764.6058600877\n",
+       "    time_coverage_start:  2021-06-01\n",
+       "    time_coverage_end:    2021-07-01</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'COPERNICUS/S2_SR_HARMONIZED'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 12</li><li><span class='xr-has-index'>band</span>: 3</li><li><span class='xr-has-index'>y</span>: 64</li><li><span class='xr-has-index'>x</span>: 64</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7995b369-563a-4c86-bb32-540c1654da76' class='xr-array-in' type='checkbox' checked><label for='section-7995b369-563a-4c86-bb32-540c1654da76' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(12, 1, 64, 64), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 576.00 kiB </td>\n",
+       "                        <td> 192.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (12, 3, 64, 64) </td>\n",
+       "                        <td> (12, 1, 64, 64) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 3 chunks in 8 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> int32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"412\" height=\"190\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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+       "  <text x=\"111.031051\" y=\"150.031051\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,111.031051,150.031051)\">3</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-3b851400-af1f-4e4b-9ca4-9539ac944bc1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3b851400-af1f-4e4b-9ca4-9539ac944bc1' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-06-02T10:17:25.474000 ... 2...</div><input id='attrs-89fcfe82-ccdb-4a98-b409-a4b366b2115a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-89fcfe82-ccdb-4a98-b409-a4b366b2115a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ff8e643-09f3-45fd-bbb4-0e91df9bac61' class='xr-var-data-in' type='checkbox'><label for='data-1ff8e643-09f3-45fd-bbb4-0e91df9bac61' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-06-02T10:17:25.474000000&#x27;, &#x27;2021-06-04T10:07:28.146000000&#x27;,\n",
+       "       &#x27;2021-06-07T10:17:25.693000000&#x27;, &#x27;2021-06-09T10:07:27.904000000&#x27;,\n",
+       "       &#x27;2021-06-12T10:17:25.192000000&#x27;, &#x27;2021-06-14T10:07:28.213000000&#x27;,\n",
+       "       &#x27;2021-06-17T10:17:25.564000000&#x27;, &#x27;2021-06-19T10:07:27.666000000&#x27;,\n",
+       "       &#x27;2021-06-22T10:17:25.574000000&#x27;, &#x27;2021-06-24T10:07:27.669000000&#x27;,\n",
+       "       &#x27;2021-06-27T10:17:25.442000000&#x27;, &#x27;2021-06-29T10:07:29.002000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.784e+05 3.785e+05 ... 3.791e+05</div><input id='attrs-23f80da8-c6bb-4223-b22a-c2c621b1b41c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-23f80da8-c6bb-4223-b22a-c2c621b1b41c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f749dbe9-27a8-40e5-bfa5-6f681e3c45f4' class='xr-var-data-in' type='checkbox'><label for='data-f749dbe9-27a8-40e5-bfa5-6f681e3c45f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([378445., 378455., 378465., 378475., 378485., 378495., 378505., 378515.,\n",
+       "       378525., 378535., 378545., 378555., 378565., 378575., 378585., 378595.,\n",
+       "       378605., 378615., 378625., 378635., 378645., 378655., 378665., 378675.,\n",
+       "       378685., 378695., 378705., 378715., 378725., 378735., 378745., 378755.,\n",
+       "       378765., 378775., 378785., 378795., 378805., 378815., 378825., 378835.,\n",
+       "       378845., 378855., 378865., 378875., 378885., 378895., 378905., 378915.,\n",
+       "       378925., 378935., 378945., 378955., 378965., 378975., 378985., 378995.,\n",
+       "       379005., 379015., 379025., 379035., 379045., 379055., 379065., 379075.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.301e+06 5.301e+06 ... 5.3e+06</div><input id='attrs-6b777a87-884a-4290-9118-3d5e81049fea' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6b777a87-884a-4290-9118-3d5e81049fea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ffd5bf6-4f01-48b1-8575-f61939d5776c' class='xr-var-data-in' type='checkbox'><label for='data-0ffd5bf6-4f01-48b1-8575-f61939d5776c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5301005., 5300995., 5300985., 5300975., 5300965., 5300955., 5300945.,\n",
+       "       5300935., 5300925., 5300915., 5300905., 5300895., 5300885., 5300875.,\n",
+       "       5300865., 5300855., 5300845., 5300835., 5300825., 5300815., 5300805.,\n",
+       "       5300795., 5300785., 5300775., 5300765., 5300755., 5300745., 5300735.,\n",
+       "       5300725., 5300715., 5300705., 5300695., 5300685., 5300675., 5300665.,\n",
+       "       5300655., 5300645., 5300635., 5300625., 5300615., 5300605., 5300595.,\n",
+       "       5300585., 5300575., 5300565., 5300555., 5300545., 5300535., 5300525.,\n",
+       "       5300515., 5300505., 5300495., 5300485., 5300475., 5300465., 5300455.,\n",
+       "       5300445., 5300435., 5300425., 5300415., 5300405., 5300395., 5300385.,\n",
+       "       5300375.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>band</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;B2&#x27; &#x27;B3&#x27; &#x27;B4&#x27;</div><input id='attrs-7287b09b-3083-44a5-ab6f-f74f8530872e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7287b09b-3083-44a5-ab6f-f74f8530872e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5bd21f8c-2322-4b63-86c4-7f8feb14b527' class='xr-var-data-in' type='checkbox'><label for='data-5bd21f8c-2322-4b63-86c4-7f8feb14b527' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;B2&#x27;, &#x27;B3&#x27;, &#x27;B4&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cubo:distance_from_center</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>445.7 438.8 432.0 ... 438.3 445.4</div><input id='attrs-9db509ab-52b9-4233-bf8d-a2e47ea71594' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9db509ab-52b9-4233-bf8d-a2e47ea71594' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f6ff9c3-9f26-4fb3-82ad-586823204860' class='xr-var-data-in' type='checkbox'><label for='data-6f6ff9c3-9f26-4fb3-82ad-586823204860' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[445.67914711, 438.76826678, 431.97833474, ..., 437.92576698,\n",
+       "        444.82206234, 451.83443528],\n",
+       "       [438.56331923, 431.53849739, 424.63297621, ..., 430.68185495,\n",
+       "        437.69230053, 444.81708566],\n",
+       "       [431.56189332, 424.42120296, 417.39794835, ..., 423.55016584,\n",
+       "        430.67671488, 437.91565683],\n",
+       "       ...,\n",
+       "       [425.21847663, 417.96942786, 410.83589471, ..., 417.08491711,\n",
+       "        424.32006532, 431.66562012],\n",
+       "       [432.10951814, 424.97802934, 417.96413145, ..., 424.10813583,\n",
+       "        431.22546381, 438.45534595],\n",
+       "       [439.12016403, 432.10439505, 425.20806434, ..., 431.24887672,\n",
+       "        438.25025206, 445.36611141]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a8a29810-1f31-475e-88c3-d30f19149433' class='xr-section-summary-in' type='checkbox'  ><label for='section-a8a29810-1f31-475e-88c3-d30f19149433' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-91473b47-9835-442a-bc30-1614e323ea5d' class='xr-index-data-in' type='checkbox'/><label for='index-91473b47-9835-442a-bc30-1614e323ea5d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2021-06-02 10:17:25.474000&#x27;, &#x27;2021-06-04 10:07:28.146000&#x27;,\n",
+       "               &#x27;2021-06-07 10:17:25.693000&#x27;, &#x27;2021-06-09 10:07:27.904000&#x27;,\n",
+       "               &#x27;2021-06-12 10:17:25.192000&#x27;, &#x27;2021-06-14 10:07:28.213000&#x27;,\n",
+       "               &#x27;2021-06-17 10:17:25.564000&#x27;, &#x27;2021-06-19 10:07:27.666000&#x27;,\n",
+       "               &#x27;2021-06-22 10:17:25.574000&#x27;, &#x27;2021-06-24 10:07:27.669000&#x27;,\n",
+       "               &#x27;2021-06-27 10:17:25.442000&#x27;, &#x27;2021-06-29 10:07:29.002000&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e56d166a-d5f6-4fb3-9d9c-a8d83eea1638' class='xr-index-data-in' type='checkbox'/><label for='index-e56d166a-d5f6-4fb3-9d9c-a8d83eea1638' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([378445.0, 378455.0, 378465.0, 378475.0, 378485.0, 378495.0, 378505.0,\n",
+       "       378515.0, 378525.0, 378535.0, 378545.0, 378555.0, 378565.0, 378575.0,\n",
+       "       378585.0, 378595.0, 378605.0, 378615.0, 378625.0, 378635.0, 378645.0,\n",
+       "       378655.0, 378665.0, 378675.0, 378685.0, 378695.0, 378705.0, 378715.0,\n",
+       "       378725.0, 378735.0, 378745.0, 378755.0, 378765.0, 378775.0, 378785.0,\n",
+       "       378795.0, 378805.0, 378815.0, 378825.0, 378835.0, 378845.0, 378855.0,\n",
+       "       378865.0, 378875.0, 378885.0, 378895.0, 378905.0, 378915.0, 378925.0,\n",
+       "       378935.0, 378945.0, 378955.0, 378965.0, 378975.0, 378985.0, 378995.0,\n",
+       "       379005.0, 379015.0, 379025.0, 379035.0, 379045.0, 379055.0, 379065.0,\n",
+       "       379075.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8795671e-ea59-4d32-88fa-c94f4bb3b0f8' class='xr-index-data-in' type='checkbox'/><label for='index-8795671e-ea59-4d32-88fa-c94f4bb3b0f8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([5301005.0, 5300995.0, 5300985.0, 5300975.0, 5300965.0, 5300955.0,\n",
+       "       5300945.0, 5300935.0, 5300925.0, 5300915.0, 5300905.0, 5300895.0,\n",
+       "       5300885.0, 5300875.0, 5300865.0, 5300855.0, 5300845.0, 5300835.0,\n",
+       "       5300825.0, 5300815.0, 5300805.0, 5300795.0, 5300785.0, 5300775.0,\n",
+       "       5300765.0, 5300755.0, 5300745.0, 5300735.0, 5300725.0, 5300715.0,\n",
+       "       5300705.0, 5300695.0, 5300685.0, 5300675.0, 5300665.0, 5300655.0,\n",
+       "       5300645.0, 5300635.0, 5300625.0, 5300615.0, 5300605.0, 5300595.0,\n",
+       "       5300585.0, 5300575.0, 5300565.0, 5300555.0, 5300545.0, 5300535.0,\n",
+       "       5300525.0, 5300515.0, 5300505.0, 5300495.0, 5300485.0, 5300475.0,\n",
+       "       5300465.0, 5300455.0, 5300445.0, 5300435.0, 5300425.0, 5300415.0,\n",
+       "       5300405.0, 5300395.0, 5300385.0, 5300375.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>band</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-87275942-d0b1-4b9d-b13e-ff80108e4216' class='xr-index-data-in' type='checkbox'/><label for='index-87275942-d0b1-4b9d-b13e-ff80108e4216' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;B2&#x27;, &#x27;B3&#x27;, &#x27;B4&#x27;], dtype=&#x27;object&#x27;, name=&#x27;band&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d6f854bb-9ebd-482b-84d9-b367921719a9' class='xr-section-summary-in' type='checkbox'  ><label for='section-d6f854bb-9ebd-482b-84d9-b367921719a9' class='xr-section-summary' >Attributes: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>collection :</span></dt><dd>COPERNICUS/S2_SR_HARMONIZED</dd><dt><span>stac :</span></dt><dd>https://earthengine-stac.storage.googleapis.com/catalog/catalog.json</dd><dt><span>epsg :</span></dt><dd>32633</dd><dt><span>resolution :</span></dt><dd>10</dd><dt><span>edge_size :</span></dt><dd>64</dd><dt><span>central_lat :</span></dt><dd>47.848151988493385</dd><dt><span>central_lon :</span></dt><dd>13.379491178028564</dd><dt><span>central_y :</span></dt><dd>5300694.38448788</dd><dt><span>central_x :</span></dt><dd>378764.6058600877</dd><dt><span>time_coverage_start :</span></dt><dd>2021-06-01</dd><dt><span>time_coverage_end :</span></dt><dd>2021-07-01</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'COPERNICUS/S2_SR_HARMONIZED' (time: 12, band: 3, y: 64, x: 64)>\n",
+       "dask.array<transpose, shape=(12, 3, 64, 64), dtype=int32, chunksize=(12, 1, 64, 64), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * time                       (time) datetime64[ns] 2021-06-02T10:17:25.4740...\n",
+       "  * x                          (x) float64 3.784e+05 3.785e+05 ... 3.791e+05\n",
+       "  * y                          (y) float64 5.301e+06 5.301e+06 ... 5.3e+06\n",
+       "  * band                       (band) object 'B2' 'B3' 'B4'\n",
+       "    cubo:distance_from_center  (y, x) float64 445.7 438.8 432.0 ... 438.3 445.4\n",
+       "Attributes:\n",
+       "    collection:           COPERNICUS/S2_SR_HARMONIZED\n",
+       "    stac:                 https://earthengine-stac.storage.googleapis.com/cat...\n",
+       "    epsg:                 32633\n",
+       "    resolution:           10\n",
+       "    edge_size:            64\n",
+       "    central_lat:          47.848151988493385\n",
+       "    central_lon:          13.379491178028564\n",
+       "    central_y:            5300694.38448788\n",
+       "    central_x:            378764.6058600877\n",
+       "    time_coverage_start:  2021-06-01\n",
+       "    time_coverage_end:    2021-07-01"
+      ]
+     },
+     "execution_count": 61,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "da = cubo.create(\n",
+    "    lat=47.848151988493385,\n",
+    "    lon=13.379491178028564,\n",
+    "    collection=\"COPERNICUS/S2_SR_HARMONIZED\", # ID of the GEE collection\n",
+    "    bands=[\"B2\",\"B3\",\"B4\"], # Bands to retrieve\n",
+    "    start_date=\"2021-06-01\",\n",
+    "    end_date=\"2021-07-01\", # End date of the cube (remember in GEE this date is not included)\n",
+    "    edge_size=64,\n",
+    "    resolution=10,\n",
+    "    gee=True # Set to True\n",
+    ")\n",
+    "da"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now let's visualize the images of the cube in RGB."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<xarray.plot.facetgrid.FacetGrid at 0x7f96b2139ca0>"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1152x648 with 15 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "(da.sel(band=[\"B4\",\"B3\",\"B2\"])/2000).clip(0,1).plot.imshow(col=\"time\",col_wrap = 5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example 2: Using `ee.ImageCollection` objects\n",
+    "\n",
+    "Now let's use `ee.ImageCollection` objects. In this case, a pre-filtered image collection."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "S2 = (ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')\n",
+    "    .filterBounds(ee.Geometry.Point(13.379491178028564,47.848151988493385))\n",
+    "    .filterDate('2021-06-01','2021-07-01')\n",
+    "    .filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE',20)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now let's retrieve the cube via `cubo`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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+       "  display: block !important;\n",
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+       "  padding-left: 0 !important;\n",
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+       "  display: contents;\n",
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+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
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+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
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+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
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+       "}\n",
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+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
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+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
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+       "  padding-bottom: 4px;\n",
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+       "  display: none;\n",
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+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
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+       "  display: inline-block;\n",
+       "  padding: 0;\n",
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+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
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+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
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+       ".xr-var-item > .xr-var-name span {\n",
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+       "  margin-bottom: 0;\n",
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+       "\n",
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+       "\n",
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+       ".xr-var-dims:hover,\n",
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+       ".xr-var-data,\n",
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+       "\n",
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+       "  grid-column: 2;\n",
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;COPERNICUS/S2_SR_HARMONIZED&#x27; (time: 5, band: 3, y: 64, x: 64)&gt;\n",
+       "dask.array&lt;transpose, shape=(5, 3, 64, 64), dtype=int32, chunksize=(5, 1, 64, 64), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "  * time                       (time) datetime64[ns] 2021-06-04T10:07:28.1460...\n",
+       "  * x                          (x) float64 3.784e+05 3.785e+05 ... 3.791e+05\n",
+       "  * y                          (y) float64 5.301e+06 5.301e+06 ... 5.3e+06\n",
+       "  * band                       (band) object &#x27;B2&#x27; &#x27;B3&#x27; &#x27;B4&#x27;\n",
+       "    cubo:distance_from_center  (y, x) float64 445.7 438.8 432.0 ... 438.3 445.4\n",
+       "Attributes:\n",
+       "    collection:           COPERNICUS/S2_SR_HARMONIZED\n",
+       "    stac:                 https://earthengine-stac.storage.googleapis.com/cat...\n",
+       "    epsg:                 32633\n",
+       "    resolution:           10\n",
+       "    edge_size:            64\n",
+       "    central_lat:          47.848151988493385\n",
+       "    central_lon:          13.379491178028564\n",
+       "    central_y:            5300694.38448788\n",
+       "    central_x:            378764.6058600877\n",
+       "    time_coverage_start:  2021-06-01\n",
+       "    time_coverage_end:    2021-07-01</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'COPERNICUS/S2_SR_HARMONIZED'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 5</li><li><span class='xr-has-index'>band</span>: 3</li><li><span class='xr-has-index'>y</span>: 64</li><li><span class='xr-has-index'>x</span>: 64</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-da517f8a-3c07-4f04-87b5-548a1f895947' class='xr-array-in' type='checkbox' checked><label for='section-da517f8a-3c07-4f04-87b5-548a1f895947' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(5, 1, 64, 64), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 240.00 kiB </td>\n",
+       "                        <td> 80.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (5, 3, 64, 64) </td>\n",
+       "                        <td> (5, 1, 64, 64) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 3 chunks in 8 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> int32 numpy.ndarray </td>\n",
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+       "  <polygon points=\"127.06210225117769,20.062102251177688 247.0621022511777,20.062102251177688 247.0621022511777,140.0621022511777 127.06210225117769,140.0621022511777\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"187.062102\" y=\"160.062102\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >64</text>\n",
+       "  <text x=\"267.062102\" y=\"80.062102\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,267.062102,80.062102)\">64</text>\n",
+       "  <text x=\"107.031051\" y=\"150.031051\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,107.031051,150.031051)\">3</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-56a6917f-5a44-4832-abc6-ca0c8614d37d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-56a6917f-5a44-4832-abc6-ca0c8614d37d' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-06-04T10:07:28.146000 ... 2...</div><input id='attrs-4e45e358-a4c7-4f4e-a118-ba3eb5c01173' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4e45e358-a4c7-4f4e-a118-ba3eb5c01173' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-927c3bc0-e95b-4b8d-93ba-75542f14b52a' class='xr-var-data-in' type='checkbox'><label for='data-927c3bc0-e95b-4b8d-93ba-75542f14b52a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-06-04T10:07:28.146000000&#x27;, &#x27;2021-06-14T10:07:28.213000000&#x27;,\n",
+       "       &#x27;2021-06-17T10:17:25.564000000&#x27;, &#x27;2021-06-22T10:17:25.574000000&#x27;,\n",
+       "       &#x27;2021-06-29T10:07:29.002000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.784e+05 3.785e+05 ... 3.791e+05</div><input id='attrs-99343076-7804-477c-b020-9b6e7eb0709b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-99343076-7804-477c-b020-9b6e7eb0709b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-468bb0e0-e66c-4427-b2ed-f234e8f13a04' class='xr-var-data-in' type='checkbox'><label for='data-468bb0e0-e66c-4427-b2ed-f234e8f13a04' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([378445., 378455., 378465., 378475., 378485., 378495., 378505., 378515.,\n",
+       "       378525., 378535., 378545., 378555., 378565., 378575., 378585., 378595.,\n",
+       "       378605., 378615., 378625., 378635., 378645., 378655., 378665., 378675.,\n",
+       "       378685., 378695., 378705., 378715., 378725., 378735., 378745., 378755.,\n",
+       "       378765., 378775., 378785., 378795., 378805., 378815., 378825., 378835.,\n",
+       "       378845., 378855., 378865., 378875., 378885., 378895., 378905., 378915.,\n",
+       "       378925., 378935., 378945., 378955., 378965., 378975., 378985., 378995.,\n",
+       "       379005., 379015., 379025., 379035., 379045., 379055., 379065., 379075.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.301e+06 5.301e+06 ... 5.3e+06</div><input id='attrs-b8a08c6b-736a-473b-91b8-565c5852058c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b8a08c6b-736a-473b-91b8-565c5852058c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-831e5017-37ed-42b3-8965-c371d573b815' class='xr-var-data-in' type='checkbox'><label for='data-831e5017-37ed-42b3-8965-c371d573b815' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5301005., 5300995., 5300985., 5300975., 5300965., 5300955., 5300945.,\n",
+       "       5300935., 5300925., 5300915., 5300905., 5300895., 5300885., 5300875.,\n",
+       "       5300865., 5300855., 5300845., 5300835., 5300825., 5300815., 5300805.,\n",
+       "       5300795., 5300785., 5300775., 5300765., 5300755., 5300745., 5300735.,\n",
+       "       5300725., 5300715., 5300705., 5300695., 5300685., 5300675., 5300665.,\n",
+       "       5300655., 5300645., 5300635., 5300625., 5300615., 5300605., 5300595.,\n",
+       "       5300585., 5300575., 5300565., 5300555., 5300545., 5300535., 5300525.,\n",
+       "       5300515., 5300505., 5300495., 5300485., 5300475., 5300465., 5300455.,\n",
+       "       5300445., 5300435., 5300425., 5300415., 5300405., 5300395., 5300385.,\n",
+       "       5300375.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>band</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;B2&#x27; &#x27;B3&#x27; &#x27;B4&#x27;</div><input id='attrs-e94146f2-f915-424b-a94e-5c8a064a6878' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e94146f2-f915-424b-a94e-5c8a064a6878' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ca1cdbd-64c8-4933-8691-0de9b41c8a0c' class='xr-var-data-in' type='checkbox'><label for='data-3ca1cdbd-64c8-4933-8691-0de9b41c8a0c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;B2&#x27;, &#x27;B3&#x27;, &#x27;B4&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cubo:distance_from_center</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>445.7 438.8 432.0 ... 438.3 445.4</div><input id='attrs-b4c1ef6e-b107-4617-9efb-18a04638a99e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b4c1ef6e-b107-4617-9efb-18a04638a99e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c81b5a19-6a50-466a-91c6-b2e3a743df8b' class='xr-var-data-in' type='checkbox'><label for='data-c81b5a19-6a50-466a-91c6-b2e3a743df8b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[445.67914711, 438.76826678, 431.97833474, ..., 437.92576698,\n",
+       "        444.82206234, 451.83443528],\n",
+       "       [438.56331923, 431.53849739, 424.63297621, ..., 430.68185495,\n",
+       "        437.69230053, 444.81708566],\n",
+       "       [431.56189332, 424.42120296, 417.39794835, ..., 423.55016584,\n",
+       "        430.67671488, 437.91565683],\n",
+       "       ...,\n",
+       "       [425.21847663, 417.96942786, 410.83589471, ..., 417.08491711,\n",
+       "        424.32006532, 431.66562012],\n",
+       "       [432.10951814, 424.97802934, 417.96413145, ..., 424.10813583,\n",
+       "        431.22546381, 438.45534595],\n",
+       "       [439.12016403, 432.10439505, 425.20806434, ..., 431.24887672,\n",
+       "        438.25025206, 445.36611141]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-654485fc-41d1-42ca-9a6b-6106e8f5dc3c' class='xr-section-summary-in' type='checkbox'  ><label for='section-654485fc-41d1-42ca-9a6b-6106e8f5dc3c' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-322b31bd-f353-4587-a062-332321771e59' class='xr-index-data-in' type='checkbox'/><label for='index-322b31bd-f353-4587-a062-332321771e59' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2021-06-04 10:07:28.146000&#x27;, &#x27;2021-06-14 10:07:28.213000&#x27;,\n",
+       "               &#x27;2021-06-17 10:17:25.564000&#x27;, &#x27;2021-06-22 10:17:25.574000&#x27;,\n",
+       "               &#x27;2021-06-29 10:07:29.002000&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5b0927cc-6cfb-4e42-92e7-d58fb42ea9b6' class='xr-index-data-in' type='checkbox'/><label for='index-5b0927cc-6cfb-4e42-92e7-d58fb42ea9b6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([378445.0, 378455.0, 378465.0, 378475.0, 378485.0, 378495.0, 378505.0,\n",
+       "       378515.0, 378525.0, 378535.0, 378545.0, 378555.0, 378565.0, 378575.0,\n",
+       "       378585.0, 378595.0, 378605.0, 378615.0, 378625.0, 378635.0, 378645.0,\n",
+       "       378655.0, 378665.0, 378675.0, 378685.0, 378695.0, 378705.0, 378715.0,\n",
+       "       378725.0, 378735.0, 378745.0, 378755.0, 378765.0, 378775.0, 378785.0,\n",
+       "       378795.0, 378805.0, 378815.0, 378825.0, 378835.0, 378845.0, 378855.0,\n",
+       "       378865.0, 378875.0, 378885.0, 378895.0, 378905.0, 378915.0, 378925.0,\n",
+       "       378935.0, 378945.0, 378955.0, 378965.0, 378975.0, 378985.0, 378995.0,\n",
+       "       379005.0, 379015.0, 379025.0, 379035.0, 379045.0, 379055.0, 379065.0,\n",
+       "       379075.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b2f9d8b2-a447-45a4-b9b1-6e4666976a7d' class='xr-index-data-in' type='checkbox'/><label for='index-b2f9d8b2-a447-45a4-b9b1-6e4666976a7d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([5301005.0, 5300995.0, 5300985.0, 5300975.0, 5300965.0, 5300955.0,\n",
+       "       5300945.0, 5300935.0, 5300925.0, 5300915.0, 5300905.0, 5300895.0,\n",
+       "       5300885.0, 5300875.0, 5300865.0, 5300855.0, 5300845.0, 5300835.0,\n",
+       "       5300825.0, 5300815.0, 5300805.0, 5300795.0, 5300785.0, 5300775.0,\n",
+       "       5300765.0, 5300755.0, 5300745.0, 5300735.0, 5300725.0, 5300715.0,\n",
+       "       5300705.0, 5300695.0, 5300685.0, 5300675.0, 5300665.0, 5300655.0,\n",
+       "       5300645.0, 5300635.0, 5300625.0, 5300615.0, 5300605.0, 5300595.0,\n",
+       "       5300585.0, 5300575.0, 5300565.0, 5300555.0, 5300545.0, 5300535.0,\n",
+       "       5300525.0, 5300515.0, 5300505.0, 5300495.0, 5300485.0, 5300475.0,\n",
+       "       5300465.0, 5300455.0, 5300445.0, 5300435.0, 5300425.0, 5300415.0,\n",
+       "       5300405.0, 5300395.0, 5300385.0, 5300375.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>band</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-22d42416-0913-444a-8874-3baec2a619b5' class='xr-index-data-in' type='checkbox'/><label for='index-22d42416-0913-444a-8874-3baec2a619b5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;B2&#x27;, &#x27;B3&#x27;, &#x27;B4&#x27;], dtype=&#x27;object&#x27;, name=&#x27;band&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bb3f39e9-d45d-4be8-8da1-52cf978aacc7' class='xr-section-summary-in' type='checkbox'  ><label for='section-bb3f39e9-d45d-4be8-8da1-52cf978aacc7' class='xr-section-summary' >Attributes: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>collection :</span></dt><dd>COPERNICUS/S2_SR_HARMONIZED</dd><dt><span>stac :</span></dt><dd>https://earthengine-stac.storage.googleapis.com/catalog/catalog.json</dd><dt><span>epsg :</span></dt><dd>32633</dd><dt><span>resolution :</span></dt><dd>10</dd><dt><span>edge_size :</span></dt><dd>64</dd><dt><span>central_lat :</span></dt><dd>47.848151988493385</dd><dt><span>central_lon :</span></dt><dd>13.379491178028564</dd><dt><span>central_y :</span></dt><dd>5300694.38448788</dd><dt><span>central_x :</span></dt><dd>378764.6058600877</dd><dt><span>time_coverage_start :</span></dt><dd>2021-06-01</dd><dt><span>time_coverage_end :</span></dt><dd>2021-07-01</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'COPERNICUS/S2_SR_HARMONIZED' (time: 5, band: 3, y: 64, x: 64)>\n",
+       "dask.array<transpose, shape=(5, 3, 64, 64), dtype=int32, chunksize=(5, 1, 64, 64), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * time                       (time) datetime64[ns] 2021-06-04T10:07:28.1460...\n",
+       "  * x                          (x) float64 3.784e+05 3.785e+05 ... 3.791e+05\n",
+       "  * y                          (y) float64 5.301e+06 5.301e+06 ... 5.3e+06\n",
+       "  * band                       (band) object 'B2' 'B3' 'B4'\n",
+       "    cubo:distance_from_center  (y, x) float64 445.7 438.8 432.0 ... 438.3 445.4\n",
+       "Attributes:\n",
+       "    collection:           COPERNICUS/S2_SR_HARMONIZED\n",
+       "    stac:                 https://earthengine-stac.storage.googleapis.com/cat...\n",
+       "    epsg:                 32633\n",
+       "    resolution:           10\n",
+       "    edge_size:            64\n",
+       "    central_lat:          47.848151988493385\n",
+       "    central_lon:          13.379491178028564\n",
+       "    central_y:            5300694.38448788\n",
+       "    central_x:            378764.6058600877\n",
+       "    time_coverage_start:  2021-06-01\n",
+       "    time_coverage_end:    2021-07-01"
+      ]
+     },
+     "execution_count": 89,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "da = cubo.create(\n",
+    "    lat=47.848151988493385,\n",
+    "    lon=13.379491178028564,\n",
+    "    collection=S2, # ee.ImageCollection object\n",
+    "    bands=['B2','B3','B4'], # Bands to retrieve\n",
+    "    start_date='2021-06-01',\n",
+    "    end_date='2021-07-01', # End date of the cube (remember in GEE this date is not included)\n",
+    "    edge_size=64,\n",
+    "    resolution=10,\n",
+    "    gee=True # Set to True\n",
+    ")\n",
+    "da"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now let's visualize the filtered images in RGB:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<xarray.plot.facetgrid.FacetGrid at 0x7f96b2be3a00>"
+      ]
+     },
+     "execution_count": 90,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1152x216 with 5 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "(da.sel(band=[\"B4\",\"B3\",\"B2\"])/2000).clip(0,1).plot.imshow(col=\"time\",col_wrap = 5)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "cubo",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/setup.py b/setup.py
index 54977c5..7b9274a 100644
--- a/setup.py
+++ b/setup.py
@@ -19,7 +19,7 @@ def read(filename):
     license="MIT",
     author="David Montero Loaiza",
     author_email="dml.mont@gmail.com",
-    description="Easily create EO mini cubes from STAC in Python",
+    description="On-Demand Earth System Data Cubes in Python",
     long_description=read("README.md"),
     long_description_content_type="text/markdown",
     packages=find_packages(exclude=("tests",)),
@@ -32,6 +32,9 @@ def read(filename):
         "stackstac>=0.4.4",
         "xarray>=2023.6.0",
     ],
+    extras_require={
+        "ee": ["xee>=0.0.6"],
+    },
     classifiers=[
         "Development Status :: 2 - Pre-Alpha",
         "License :: OSI Approved :: MIT License",