Merge pull request #1536 from shivanip32/updated_cline_nbk

Updated sample notebooks: coastline extraction and LULC classification using sparse training data

Author: priyankatuteja

samples/04_gis_analysts_data_scientists/coastline_extraction-usa-landsat8_multispectral_imagery.ipynb

@@ -4,14 +4,15 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Coastline extraction using Landsat-8 multispectral imagery and band ratio technique"
+    "## Coastline extraction using Landsat-8 multispectral imagery and band ratio technique"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Table of Contents\n",
+    "* [Prerequisites](#20)\n",
     "* [Introduction](#1)\n",
     "* [Necessary imports](#2)\n",
     "* [Connect to your GIS](#3)\n",
@@ -33,6 +34,15 @@
     "* [Data resources](#19)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Prerequisites<a class=\"anchor\" id=\"20\"></a>\n",
+    "\n",
+    "- This sample demonstrates how the coastlines can be extracted using [ArcGIS Image Server](https://www.esri.com/en-us/arcgis/products/arcgis-image-server). Alternatively, this can be done using [ArcGIS Image for ArcGIS Online](https://www.esri.com/en-us/arcgis/products/arcgis-image/options/arcgis-online)."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -1133,7 +1143,8 @@
    "source": [
     "## Get the polygon with largest area as it will represent the coastline\n",
     "df = water_poly.layers[0].query().sdf\n",
-    "dfm5 = df[df['SHAPE__Area']==df['SHAPE__Area'].max()]\n",
+    "df['MYAREA'] = df.SHAPE.geom.area\n",
+    "dfm5 = df[df['MYAREA']==df['MYAREA'].max()]\n",
     "coast_poly = gis2.content.import_data(dfm5, title='coast_poly'+str(datetime.now().microsecond))"
    ]
   },
@@ -1400,7 +1411,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -1414,7 +1425,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.11"
+   "version": "3.9.11"
   }
  },
  "nbformat": 4,