From ec3a8818d297ff5bac023fab79c12e188e712501 Mon Sep 17 00:00:00 2001 From: Carl Boettiger Date: Sun, 27 Oct 2024 03:46:20 +0000 Subject: [PATCH] :artificial_satellite: --- myst.yml | 1 + reading/spatial-3.ipynb | 249 ++++++++++++++++------------------- reading/spatial-4.ipynb | 281 ++++++++++++++++++++++++++++++++++++++++ reading/spatial-5.ipynb | 67 ++++++++++ 4 files changed, 459 insertions(+), 139 deletions(-) create mode 100644 reading/spatial-4.ipynb create mode 100644 reading/spatial-5.ipynb diff --git a/myst.yml b/myst.yml index 3f08027..0299e7f 100644 --- a/myst.yml +++ b/myst.yml @@ -32,6 +32,7 @@ project: - file: reading/07-ibis-4.ipynb - file: reading/spatial-1.ipynb - file: reading/spatial-2.ipynb + - file: reading/spatial-3.ipynb site: template: book-theme diff --git a/reading/spatial-3.ipynb b/reading/spatial-3.ipynb index 4927fbe..020a114 100644 --- a/reading/spatial-3.ipynb +++ b/reading/spatial-3.ipynb @@ -14,17 +14,31 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 1, "id": "48b9cd7b-9470-45c8-8fb5-34dc03086fed", "metadata": {}, "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "bd499559c70a43e6a19d6555bb8fa19e", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "FloatProgress(value=0.0, layout=Layout(width='auto'), style=ProgressStyle(bar_color='black'))" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "data": { "text/plain": [ "array([-72.99321, 41.23109, -72.85227, 41.37502])" ] }, - "execution_count": 16, + "execution_count": 1, "metadata": {}, "output_type": "execute_result" } @@ -49,6 +63,8 @@ "id": "3c9f9ac1-2f26-42ab-b0dd-7365fa494541", "metadata": {}, "source": [ + "## STAC Search\n", + "\n", "Working with raster data will take us beyond the tabular data model we have been using so far with `ibis` into another data model, known in some communities as \"raster\" data and others as \"M-dimensional array data\". Consequently, we will be introducing a suite of new packages for working with kind of data. To help associate the different new python packages with there roles in this data pipeline, I will be adding the `import` commands as we go along, rather than all at once. \n", "\n", "\n", @@ -101,7 +117,7 @@ { "cell_type": "code", "execution_count": 4, - "id": "17fd6259-81dc-4017-9683-36f27e22d0b0", + "id": "2e5c432c-60a0-4eaf-af39-6b65d5b30b5f", "metadata": {}, "outputs": [ { @@ -47338,7 +47354,7 @@ "" ], "text/plain": [ - "" + "" ] }, "execution_count": 4, @@ -47350,6 +47366,39 @@ "items" ] }, + { + "attachments": { + "7d519282-31e3-47ee-b30c-c353f8162082.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "id": "6e22d38b-298e-428f-976a-ce44654532b2", + "metadata": {}, + "source": [ + "Our catalog search has returned four items, or \"features\", each corresponding to a different time the satellite has flown over and taken an image of our bounding box during the window described. Our search criteria have also excluded any images taken during that interval that have more than 20% cloud cover. You may need to adjust the cloud cover filter or the date range to recover a handful of images. We need at least one, but preferably a few different images to get an accurate estimate of the greenness during summer months. Too many images, however, can just bog things down with exta calculations. If you have more than 4 or 5 images, consider a stricter cloud requirement or a narrower date range to filter down your results. \n", + "\n", + "\n", + "Click on the arrows above to drill down into the list of features returned like so:\n", + "\n", + "![image.png](attachment:7d519282-31e3-47ee-b30c-c353f8162082.png)\n", + "\n", + "Within each \"feature\" we find detailed metadata about the data contained. The spatial extent of the image appears in the \"geometry\", while date and other information appear under \"properties\" In the \"assets\" element, we finally find a list of all the individual data files associated with this feature -- primarily specific \"bands\" or wavelengths of light that the cameras on board the satellite are able to detect. While cameras in smart-phones (and most small commericial cube-sats) can only see Red, Green, and Blue, the sensors on board Sentinel-2 can see in quite a lot more wavelengths. A URL points to the specific TIF file containing the data for each wavelength. " + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "2c13a231-50c1-4338-9af6-e3e62aaf2117", + "metadata": {}, + "source": [ + "## STAC to xarray\n", + "\n", + "Rather than work our way though all this metadata manually, we will now draw upon another package that is capable of understanding the information returned by the STAC catalog and helping us access only the parts we need, without downloading entire assets. Historically this kind of trick was only done with specialized systems and powerful computers such as Google Earth Engine. Today, open source tools in python make many of the same operations possible with greater flexibility and control. This approach is fundamental to scalable 'cloud-native' analysis of massive satellite data.\n", + "\n", + "Our next step uses a package called `odc.stac` to load just the two spectral bands of interest for us, and access only those parts of each file that correspond to our area of interest. We will only scratch the surface of `odc.stac` tooling here, but more details can be found in the [odc.stac documentation](https://odc-stac.readthedocs.io/en/latest/intro.html)." + ] + }, { "cell_type": "code", "execution_count": 5, @@ -47371,7 +47420,7 @@ " items,\n", " bands=[\"nir08\", \"red\"],\n", " bbox=box,\n", - " chunks = {}\n", + " chunks = {} # this tells odc to use dask\n", ")" ] }, @@ -47762,9 +47811,9 @@ " * time (time) datetime64[ns] 32B 2024-06-15T15:51:53.600000 ... 202...\n", "Data variables:\n", " nir08 (time, y, x) uint16 16MB dask.array<chunksize=(1, 1627, 1220), meta=np.ndarray>\n", - " red (time, y, x) uint16 16MB dask.array<chunksize=(1, 1627, 1220), meta=np.ndarray>