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Fixed notebooks links that were broken due to my previous changes (#1162
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* Added the sensor name Oli Tirs to the end of the Landsat 9 product URLs to make it consistent

* Changing case of 'Tools' in links to fix broken links

* Fixing some miscellaneous broken links

* Fixing one link (casing)

* Fixing 3 links

* Fixed a waterbodies link

* Reverted data_tools source (.py) links back to relative links so that they will open in a tab in the Jupyter Notebook

* Reverted another data tools Python link

* Reverted some remaining links to be .py links

* Fixed one Scalable machine learning relative link

* Fixed several more links - 19 Dec

---------

Co-authored-by: Benjamin Glitsos <[email protected]>
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benji-glitsos-ga and Benjamin Glitsos authored Dec 19, 2023
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2 changes: 1 addition & 1 deletion Beginners_guide/01_Jupyter_notebooks.ipynb
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"\n",
"To rename this notebook to something more useful, right-click on it in the file browser and select \"Rename\".\n",
"\n",
"> **Note:** The `dea-notebooks` repository provides a **template notebook** containing a consistent structure and style that is recommended for all DEA Jupyter notebooks. To use this template rather than start a notebook from scratch, click [this link to open the \"DEA_notebooks_template.ipynb\"](../../DEA_notebooks_template.ipynb) notebook, then click \"File\" and \"Save Notebook As...\" to create a copy of the template in your desired location."
"> **Note:** The `dea-notebooks` repository provides a **template notebook** containing a consistent structure and style that is recommended for all DEA Jupyter notebooks. To use this template rather than start a notebook from scratch, click [this link to open the \"DEA_notebooks_template.ipynb\"](https://github.com/GeoscienceAustralia/dea-notebooks/blob/develop/DEA_notebooks_template.ipynb) notebook, then click \"File\" and \"Save Notebook As...\" to create a copy of the template in your desired location."
]
},
{
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6 changes: 3 additions & 3 deletions Beginners_guide/05_Plotting.ipynb
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"source": [
"## Description\n",
"This introductory notebook demonstrates how to visualise DEA satellite data returned from running a datacube query.\n",
"The notebook demonstrates commonly used `xarray` plotting methods, as well as custom functions provided in the [dea_tools.plotting](https://docs.dea.ga.gov.au/notebooks/tools/gen/dea_tools.plotting/) module.\n",
"The notebook demonstrates commonly used `xarray` plotting methods, as well as custom functions provided in the [dea_tools.plotting](../Tools/dea_tools/plotting.py) module.\n",
"\n",
"Topics covered in this notebook include:\n",
"\n",
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"source": [
"### Load packages\n",
"The first step is to run `%matplotlib inline`, which ensures figures plot correctly in the Jupyter notebook.\n",
"Next, load the `datacube` package to enable loading data, and a selection of custom DEA functions from the [dea_tools.plotting](https://docs.dea.ga.gov.au/notebooks/tools/gen/dea_tools.plotting/) module."
"Next, load the `datacube` package to enable loading data, and a selection of custom DEA functions from the [dea_tools.plotting](../Tools/dea_tools/plotting.py) module."
]
},
{
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"\n",
"For advanced plotting and visualisation options, see:\n",
"\n",
"* The [dea_tools.plotting](https://docs.dea.ga.gov.au/notebooks/tools/gen/dea_tools.plotting/) module containing functions used for plotting and visualising DEA data.\n",
"* The [dea_tools.plotting](../Tools/dea_tools/temporal.py) module containing functions used for plotting and visualising DEA data.\n",
"\n",
"Once you have you have completed the beginner tutorials, join advanced users in exploring:\n",
"\n",
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4 changes: 2 additions & 2 deletions DEA_notebooks_template.ipynb
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"* Use the [PEP8 standard](https://www.python.org/dev/peps/pep-0008/) for code. To make sure all code in the notebook is consistent, you can use the `jupyterlab_code_formatter` tool: select each code cell, then click `Edit` and then one of the `Apply X Formatter` options (`YAPF` or `Black` are recommended). This will reformat the code in the cell to a consistent style.\n",
"* For additional guidance, refer to the style conventions and layouts in approved `develop` branch notebooks. Examples include:\n",
" * [How_to_guides/Using_load_ard.ipynb](../How_to_guides/Using_load_ard.ipynb)\n",
" * [Real_world_examples/Coastal_erosion.ipynb](./Real_world_examples/Coastal_erosion.ipynb)\n",
" * [Tools/dea_tools/datahandling.py](./Tools/dea_tools/datahandling.py)\n",
" * [Real_world_examples/Coastal_erosion.ipynb](../Real_world_examples/Coastal_erosion.ipynb)\n",
" * [Tools/dea_tools/datahandling.py](../Tools/dea_tools/datahandling.py)\n",
"* In the final notebook cell, include a set of relevant tags which are used to build the DEA User Guide's [Tag Index](https://docs.dea.ga.gov.au/genindex/). \n",
"Use all lower-case (unless the tag is an acronym), separate words with spaces (unless it is the name of an imported module), and [re-use existing tags](https://github.com/GeoscienceAustralia/dea-notebooks/wiki/List-of-tags).\n",
"Ensure the tags cell below is in `Raw` format, rather than `Markdown` or `Code`.\n",
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2 changes: 1 addition & 1 deletion DEA_products/DEA_Land_Cover.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"In the following sections, we will plot data using the `plot_land_cover()` function. More details about the function can be found in [land_cover.py](https://docs.dea.ga.gov.au/notebooks/tools/gen/dea_tools.landcover/)."
"In the following sections, we will plot data using the `plot_land_cover()` function. More details about the function can be found in [landcover.py](../Tools/dea_tools/landcover.py)."
]
},
{
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6 changes: 3 additions & 3 deletions DEA_products/DEA_Landsat_Surface_Reflectance.ipynb
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"\n",
"It contains three sub-products that provide corrections or attribution information:\n",
"\n",
"* Surface Reflectance NBAR ([Landsat 5 TM](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbar-landsat-5-tm), [Landsat 7 ETM+](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbar-landsat-7-etm), [Landsat 8 OLI-TIRS](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbar-landsat-8-oli-tirs), [Landsat 9 OLI-TIRS](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbar-landsat-9))\n",
"* Surface Reflectance NBART ([Landsat 5 TM](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbart-landsat-5-tm), [Landsat 7 ETM+](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbart-landsat-7-etm), [Landsat 8 OLI-TIRS](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbart-landsat-8-oli-tirs), [Landsat 9 OLI-TIRS](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbart-landsat-9))\n",
"* Surface Reflectance Observation Attributes (OA) ([Landsat 5 TM](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-oa-landsat-5-tm), [Landsat 7 ETM+](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-oa-landsat-7-etm), [Landsat 8 OLI-TIRS](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-oa-landsat-8-oli-tirs), [Landsat 9 OLI-TIRS](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-oa-landsat-9))\n",
"* Surface Reflectance NBAR ([Landsat 5 TM](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbar-landsat-5-tm), [Landsat 7 ETM+](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbar-landsat-7-etm), [Landsat 8 OLI-TIRS](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbar-landsat-8-oli-tirs), [Landsat 9 OLI-TIRS](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbar-landsat-9-oli-tirs/))\n",
"* Surface Reflectance NBART ([Landsat 5 TM](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbart-landsat-5-tm), [Landsat 7 ETM+](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbart-landsat-7-etm), [Landsat 8 OLI-TIRS](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbart-landsat-8-oli-tirs), [Landsat 9 OLI-TIRS](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-nbart-landsat-9-oli-tirs/))\n",
"* Surface Reflectance Observation Attributes (OA) ([Landsat 5 TM](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-oa-landsat-5-tm), [Landsat 7 ETM+](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-oa-landsat-7-etm), [Landsat 8 OLI-TIRS](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-oa-landsat-8-oli-tirs), [Landsat 9 OLI-TIRS](https://docs.dea.ga.gov.au/data/product/dea-surface-reflectance-oa-landsat-9-oli-tirs/))\n",
"\n",
"The resolution is a 30 m grid based on the USGS Landsat Collection 1 archive.\n",
"\n",
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8 changes: 4 additions & 4 deletions DEA_products/DEA_Wetlands_Insight_Tool.ipynb
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"Licencing information is provided at the bottom of this notebook, and requires attribution.** \n",
"\n",
"## Related products\n",
"* [DEA Fractional Cover (Landsat)](https://docs.dea.ga.gov.au/notebooks/DEA_products/DEA_Fractional_Cover.ipynb)\n",
"* [DEA Fractional Cover (Landsat)](../DEA_products/DEA_Fractional_Cover.ipynb)\n",
"* [DEA Tasseled Cap Indices Percentiles Calendar Year (Landsat)](https://docs.dea.ga.gov.au/data/product/dea-wetness-percentiles-landsat)\n",
"* [DEA Water Observations (Landsat)](https://docs.dea.ga.gov.au/notebooks/DEA_products/DEA_Water_Observations/)"
"* [DEA Water Observations (Landsat)](../DEA_products/DEA_Water_Observations.ipynb)"
]
},
{
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"Loading 8 time steps\n",
"```\n",
"\n",
"For further information on the functions used here, go to the [function documentation](https://github.com/GeoscienceAustralia/dea-notebooks/blob/b13f020f8a41c30bc1bb4120ce492098a25a2bfa/Tools/dea_tools/datahandling.py)."
"For further information on the functions used here, go to the [function documentation](../Tools/dea_tools/datahandling.py)."
]
},
{
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"\n",
"1. Mask pixels not in the polygon\n",
"\n",
"2. Use the [Water Observations bit flags](https://github.com/GeoscienceAustralia/dea-notebooks/blob/develop/DEA_products/DEA_Water_Observations.ipynb) to mask noncontiguous data, low solar incidence angle, cloud, and water out of the `wet` category. We distinguish `open water` from `wet` as mutually exclusive categories. \n",
"2. Use the [Water Observations bit flags](../DEA_products/DEA_Water_Observations.ipynb) to mask noncontiguous data, low solar incidence angle, cloud, and water out of the `wet` category. We distinguish `open water` from `wet` as mutually exclusive categories. \n",
"\n",
"## Thresholding\n",
"\n",
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2 changes: 1 addition & 1 deletion How_to_guides/Detecting_seasonality.ipynb
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"* **[Sign up to the DEA Sandbox](https://app.sandbox.dea.ga.gov.au/)** to run this notebook interactively from a browser\n",
"* **Compatibility:** Notebook currently compatible with both the `NCI` and `DEA Sandbox` environments\n",
"* **Products used:** \n",
"[DEA Waterbodies](https://docs.dea.ga.gov.au/data/product/waterboards)\n"
"[DEA Waterbodies](https://docs.dea.ga.gov.au/data/product/dea-waterbodies-landsat)\n"
]
},
{
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2 changes: 1 addition & 1 deletion How_to_guides/Downloading_data_with_STAC.ipynb
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"metadata": {},
"source": [
"## Background\n",
"Digital Earth Australia (DEA) stores a range of data products on [Amazon Web Service's Simple Cloud Storage (S3)](https://docs.dea.ga.gov.au/guides/setup/aws/data_and_metadata/) with free public access. These products can be browsed on the interactive [DEA Sandbox Explorer](https://explorer.sandbox.dea.ga.gov.au/products). To make it easier to find data in the DEA archive, the DEA Sandbox Explorer also provides a [SpatioTemporal Asset Catalog (STAC)](https://stacspec.org/) endpoint for listing or searching metadata (https://explorer.sandbox.dea.ga.gov.au/stac/).\n",
"Digital Earth Australia (DEA) stores a range of data products on [Amazon Web Service's Simple Cloud Storage (S3)](https://docs.dea.ga.gov.au/guides/setup/AWS/data_and_metadata/) with free public access. These products can be browsed on the interactive [DEA Sandbox Explorer](https://explorer.sandbox.dea.ga.gov.au/products). To make it easier to find data in the DEA archive, the DEA Sandbox Explorer also provides a [SpatioTemporal Asset Catalog (STAC)](https://stacspec.org/) endpoint for listing or searching metadata (https://explorer.sandbox.dea.ga.gov.au/stac/).\n",
"\n",
"STAC is a recently developed specification that provides a common language to describe geospatial information so it can more easily be indexed and discovered. \n",
"DEA's STAC metadata can be used to quickly identify all available data for a given product, location or time period. \n",
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2 changes: 1 addition & 1 deletion How_to_guides/Generating_composites.ipynb
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"source": [
"To get an image at a certain time, often there is missing data, due to clouds and other masking. We can fill in these gaps by using data from surrounding times.\n",
"\n",
"To generate these images, we can use the custom functions `first`, `last` and `nearest` from the [dea_datahandling](https://docs.dea.ga.gov.au/notebooks/tools/gen/dea_tools.datahandling/) script.\n",
"To generate these images, we can use the custom functions `first`, `last` and `nearest` from the [datahandling](../Tools/dea_tools/datahandling.py) script.\n",
"\n",
"You can also use the in-built `.first()` and `.last()` methods when doing `groupby` and `resample` as described above. They are described in the [xarray documentation](http://xarray.pydata.org/en/stable/groupby.html#first-and-last) on grouped data."
]
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2 changes: 1 addition & 1 deletion How_to_guides/Generating_geomedian_composites.ipynb
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"source": [
"## Load Landsat 8 from the datacube\n",
"\n",
"Here we are loading in a timeseries of cloud-masked Landsat 8 satellite images through the datacube API using the [load_ard](https://github.com/GeoscienceAustralia/dea-notebooks/blob/develop/How_to_guides/Using_load_ard.ipynb) function. \n",
"Here we are loading in a timeseries of cloud-masked Landsat 8 satellite images through the datacube API using the [load_ard](../How_to_guides/Using_load_ard.ipynb) function. \n",
"This will provide us with some data to work with. To limit computation and memory this example uses only three optical bands (red, green, blue)."
]
},
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2 changes: 1 addition & 1 deletion How_to_guides/Image_segmentation.ipynb
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"source": [
"## Load Sentinel 2 data from the datacube\n",
"\n",
"Here we are loading in a timeseries of `Sentinel 2` satellite images through the datacube API using the [load_ard](https://github.com/GeoscienceAustralia/dea-notebooks/blob/develop/How_to_guides/Using_load_ard.ipynb) function. This will provide us with some data to work with."
"Here we are loading in a timeseries of `Sentinel 2` satellite images through the datacube API using the [load_ard](../How_to_guides/Using_load_ard.ipynb) function. This will provide us with some data to work with."
]
},
{
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2 changes: 1 addition & 1 deletion How_to_guides/Land_cover_animated_plots.ipynb
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"## Modifying `lc_animation()`\n",
"`lc_animation()` contains many optional parameters allowing customisation of the appearance of the land cover animations. \n",
"Below are examples of how some of them operate. \n",
"For the full details of the parameters please refer to the [land_cover.py](https://docs.dea.ga.gov.au/notebooks/tools/gen/dea_tools.landcover/) file.\n"
"For the full details of the parameters please refer to the [landcover.py](../Tools/dea_tools/landcover.py) file.\n"
]
},
{
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4 changes: 2 additions & 2 deletions How_to_guides/Machine_learning_with_ODC.ipynb
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"source": [
"## Description\n",
"\n",
"This notebook demonstrates a potential workflow using functions from the [dea_tools.classification](../Tools/gen/dea_tools.classification.ipynb) script to implement a supervised learning landcover classifier within the [ODC (Open Data Cube)](https://www.opendatacube.org.ipynb) framework. \n",
"This notebook demonstrates a potential workflow using functions from the [dea_tools.classification](../Tools/dea_tools/classification.py) script to implement a supervised learning landcover classifier within the [ODC (Open Data Cube)](https://www.opendatacube.org.ipynb) framework. \n",
"\n",
"For larger model training and prediction implementations this notebook can be adapted into a Python file and run in a distributed fashion.\n",
"\n",
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"cell_type": "markdown",
"metadata": {},
"source": [
"Once the data has been loaded, we can classify it using DEA [predict_xr](../Tools/gen/dea_tools.classification.ipynb) function:"
"Once the data has been loaded, we can classify it using DEA [predict_xr](../Tools/dea_tools/classification.py) function:"
]
},
{
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