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add living atlas guidelines note to appropriate guides #2404

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6 changes: 4 additions & 2 deletions guide/04-feature-data-and-analysis/working-with-feature-layers-and-features.ipynb
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"source": [
"<a id=\"querying-layers\"></a>\n",
"## Querying feature layers\n",
"Querying is a powerful operation that can be performed on a `FeatureLayer` object. Let's take a closer look here. To write meaningful queries, we need to know the names of fields present in the layer. This can be determined by calling the `fields` property:"
"Querying is a powerful operation that can be performed on a [`FeatureLayer`](/python/latest/api-reference/arcgis.features.toc.html#arcgis.features.FeatureLayer) object. Let's take a closer look here. To write meaningful queries, we need to know the names of fields present in the layer. This can be determined by calling the `fields` property:\n",
"\n",
"> **Note:** When leveraging Esri hosted content, organizations should review the [ArcGIS Online terms of use](https://doc.arcgis.com/en/arcgis-online/reference/terms-of-use.htm), as well as the terms of use for the data layer to ensure they are in compliance with extracting data and/or making it available in other systems."
]
},
{
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.0"
"version": "3.13.2"
},
"toc": {
"base_numbering": 1,
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8 changes: 6 additions & 2 deletions ...ith-the-spatially-enabled-dataframe/introduction-to-the-spatially-enabled-dataframe.ipynb
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"\n",
"The SEDF integrates with Esri's [`ArcPy` site-package](http://pro.arcgis.com/en/pro-app/arcpy/get-started/what-is-arcpy-.htm) as well as the open source [`pyshp`](https://github.com/GeospatialPython/pyshp/), [`shapely`](https://github.com/Toblerity/Shapely) and [`fiona`](https://github.com/Toblerity/Fiona) packages. This means the ArcGIS API for Python SEDF can use either of these geometry engines to provide you options for easily working with geospatial data regardless of your platform. The SEDF transforms data into the formats you desire so you can use Python functionality to analyze and visualize geographic information.\n",
"\n",
"Data can be read and scripted to automate workflows and just as easily visualized on maps in [`Jupyter Lab notebooks`](../using-the-jupyter-notebook-environment/). The SEDF can export data as feature classes or publish them directly to servers for sharing according to your needs. Let's explore some of the different options available with the versatile `Spatial Enabled DataFrame` namespaces:\n"
"Data can be read and scripted to automate workflows and just as easily visualized on maps in [`Jupyter Lab notebooks`](../using-the-jupyter-notebook-environment/). The SEDF can export data as feature classes or publish them directly to servers for sharing according to your needs. \n",
"\n",
"> **_Note:_** When leveraging Esri hosted content, organizations should review the [ArcGIS Online terms of use](https://doc.arcgis.com/en/arcgis-online/reference/terms-of-use.htm), as well as the terms of use for the data layer to ensure they are in compliance with extracting data and/or making it available in other systems.\n",
"\n",
"Let's explore some of the different options available with the versatile `Spatial Enabled DataFrame` namespaces:"
]
},
{
Expand Down Expand Up @@ -1418,7 +1422,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.0"
"version": "3.13.2"
},
"toc": {
"base_numbering": 1,
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6 changes: 4 additions & 2 deletions guide/05-working-with-the-spatially-enabled-dataframe/part1_introduction_to_sedf.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"> _Note:_ Spatial Data Engineering using SeDF builds on top of core Data Engineering concepts in Python. If you are new to Pandas, NumPy and related libraries, we recommend you start with the [Introduction to Data Engineering](../part1-introduction-to-dataengineering) guide series and then come here.\n"
"> _**Note:**_ Spatial Data Engineering using SeDF builds on top of core Data Engineering concepts in Python. If you are new to Pandas, NumPy and related libraries, we recommend you start with the [Introduction to Data Engineering](../part1-introduction-to-dataengineering) guide series and then come here.\n",
"\n",
"> **_Note:_** When leveraging Esri hosted content, organizations should review the [ArcGIS Online terms of use](https://doc.arcgis.com/en/arcgis-online/reference/terms-of-use.htm), as well as the terms of use for the data layer to ensure they are in compliance with extracting data and/or making it available in other systems."
]
},
{
Expand Down Expand Up @@ -1543,7 +1545,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.0"
"version": "3.13.2"
},
"toc": {
"base_numbering": 1,
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6 changes: 4 additions & 2 deletions guide/06-imagery-and-raster-analysis/using-raster-analysis.ipynb
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"\n",
"Raster Analysis can be used to create and execute spatial analysis models and image processing chains which leverage distributed storage and analysis. This powerful capability is available with ArcGIS Enterprise, and enables scalable raster analysis including terrain analysis, suitability analysis, vegetation analysis as well as persistent imagery product generation.\n",
"\n",
"The `arcgis.raster.analytics` module provides the raster analysis functionality. This module contains functions that enable you to call raster analysis tools in your GIS."
"The [`arcgis.raster.analytics`](/python/latest/api-reference/arcgis.raster.analytics.html) submodule provides the raster analysis functionality. This module contains functions that enable you to call raster analysis tools in your GIS.\n",
"\n",
"> _**Note:**_ When leveraging Esri hosted content, organizations should review the [ArcGIS Online terms of use](https://doc.arcgis.com/en/arcgis-online/reference/terms-of-use.htm), as well as the terms of use for the data layer to ensure they are in compliance with extracting data and/or making it available in other systems."
]
},
{
Expand Down Expand Up @@ -414,7 +416,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.0"
"version": "3.13.2"
},
"toc": {
"base_numbering": 1,
Expand Down