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Update product and band names in ML notebook Machine_learning_with_ODC (#1276) #1278

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Update product and band names in ML notebook Machine_learning_with_ODC (#1276) #1278

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009b792
update product and band names used in notebook
jennaguffogg Jan 15, 2025
2a3bda2
update geoMAD product and band names
jennaguffogg Jan 16, 2025
6a8f471
change hyperlink to match updated geoMAD product
jennaguffogg Jan 16, 2025
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10 changes: 5 additions & 5 deletions How_to_guides/Machine_learning_with_ODC.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@
"* **[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",
"[ga_ls8c_nbart_gm_cyear_3](https://explorer.dea.ga.gov.au/ga_ls8c_nbart_gm_cyear_3)\n",
"[ga_ls8cls9c_gm_cyear_3](https://explorer.dea.ga.gov.au/products/ga_ls8cls9c_gm_cyear_3)\n",
"* **Special requirements:** A shapefile of labelled data in shapefile format is required to use this notebook.\n",
"An example dataset is provided.\n",
"* **Prerequisites:** A basic understanding of supervised learning techniques is required. \n",
Expand Down Expand Up @@ -510,7 +510,7 @@
"source": [
"The following function is passed to `collect_training_data`. \n",
"\n",
"It extracts bands from the [ga_ls8c_nbart_gm_cyear_3](https://explorer.dea.ga.gov.au/products/ga_ls8c_nbart_gm_cyear_3) product as feature layers along side our labelled data so we can train a supervised model.\n",
"It extracts bands from the [ga_ls8cls9c_gm_cyear_3](https://explorer.dea.ga.gov.au/products/ga_ls8cls9c_gm_cyear_3) product as feature layers along side our labelled data so we can train a supervised model.\n",
"\n",
"The feature function can be modified to extract different combinations of features within the datacube, it is one of the important parts to experiment with when generating your own model."
]
Expand All @@ -527,7 +527,7 @@
" dc = datacube.Datacube(app='custom_feature_layers')\n",
"\n",
" # Load data using query\n",
" result = dc.load(product='ga_ls8c_nbart_gm_cyear_3', **query)\n",
" result = dc.load(product='ga_ls8cls9c_gm_cyear_3', **query)\n",
"\n",
" return result"
]
Expand Down Expand Up @@ -658,7 +658,7 @@
"source": [
"This section automatically creates a list of variable names and their respective indices for each of the training data variables.\n",
"\n",
"> **Note:** To use a custom subset of the satellite bands loaded above to train our data, you can replace `column_names[1:]` with a list of selected band names (e.g. `['red', 'green', 'blue']`)"
"> **Note:** To use a custom subset of the satellite bands loaded above to train our data, you can replace `column_names[1:]` with a list of selected band names (e.g. `['nbart_red', 'nbart_green', 'nbart_blue']`)"
]
},
{
Expand Down Expand Up @@ -1386,7 +1386,7 @@
" add_colorbar=False)\n",
"\n",
"# Plot true colour image\n",
"(input_data[['red', 'green', 'blue']]\n",
"(input_data[['nbart_red', 'nbart_green', 'nbart_blue']]\n",
" .squeeze('time')\n",
" .to_array()\n",
" .plot.imshow(ax=axes[1], robust=True, add_labels=False))\n",
Expand Down
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