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Updates Using_PySTAC notebook
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02_Software_Tools/01_Data_Manipulation_Tools.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.3"
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"version": "3.12.4"
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}
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},
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"nbformat": 4,

02_Software_Tools/02_Data_Visualization_Tools.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.3"
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"version": "3.12.4"
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}
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},
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"nbformat": 4,

03_Using_NASA_EarthData/03_Using_PySTAC.ipynb

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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "bea8016e-e6c2-4cc8-a53f-191c00dc33d3",
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"id": "0097891e-d381-4ce9-9258-feb7bff46992",
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"metadata": {
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"jupyter": {
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"source_hidden": true
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}
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},
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"source": [
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"There is an abundance of data searchable through NASA's [Earthdata Search](https://search.earthdata.nasa.gov). The preceding link connects to a GUI for searching [SpatioTemporal Asset Catalogs (STAC)](https://stacspec.org/) by specifying an *Area of Interest (AOI)* and a *time-window* or *range of dates*."
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"There is an abundance of data searchable through NASA's [Earthdata Search](https://search.earthdata.nasa.gov). The preceding link connects to a GUI for searching [SpatioTemporal Asset Catalogs (STAC)](https://stacspec.org/) by specifying an *Area of Interest (AOI)* and a *time-window* or *range of dates*.\n",
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"\n",
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"For the sake of reproducibility, we want to be able to search asset catalogs programmatically. This is where the [PySTAC](https://pystac.readthedocs.io/en/stable/) library comes in."
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]
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},
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{
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"cell_type": "markdown",
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"id": "b6d78912-a7d8-4e7c-8ead-ef1e593f8706",
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"metadata": {
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"jupyter": {
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"source_hidden": true
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}
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},
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"id": "4a332d11-9b60-49af-94f2-671f725414ed",
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"metadata": {},
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"source": [
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"For the sake of reproducibility, we want to be able to search asset catalogs programmatically. This is where the [PySTAC](https://pystac.readthedocs.io/en/stable/) library comes in.\n",
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"\n",
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"---"
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]
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},
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"outputs": [],
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"source": [
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"basemap = gv.tile_sources.OSM\n",
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"rect = gv.Rectangles([aoi]).opts(opts.Rectangles(alpha=0.25, color='cyan'))\n",
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"rect = gv.Rectangles([aoi]).opts(opts.Rectangles(alpha=0.15, color='cyan'))\n",
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"\n",
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"rect*basemap"
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]
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"cell_type": "code",
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"execution_count": null,
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"id": "3b863c36",
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"metadata": {},
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"metadata": {
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"jupyter": {
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"source_hidden": true
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}
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},
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"outputs": [],
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"source": [
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"len(granules.index.unique()) / len(granules) # Notice the timestamps are not all unique, i.e., some are repeated"
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.3"
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"version": "3.12.4"
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}
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},
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"nbformat": 4,

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