geemap_tutorial.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ee\n",
    "import geemap\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "88ade5313dd94ad6ad67747234af1ac5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output(layout=Layout(width='815px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "geemap.show_youtube('_6JOA-iiEGU')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "87977065895547edb3d9df89695588a5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[40, -100], controls=(WidgetControl(options=['position'], widget=HBox(children=(ToggleButton(value=…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Map = geemap.Map()\n",
    "Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "image = ee.Image('LE7_TOA_5YEAR/1999_2003')\n",
    "\n",
    "landsat_vis = {\n",
    "    'bands': ['B4', 'B3', 'B2'], \n",
    "    'gamma': 1.4\n",
    "}\n",
    "Map.addLayer(image, landsat_vis, \"LE7_TOA_5YEAR/1999_2003\", True, 0.7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Extract pixels as a Numpy array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(373, 531, 3)\n"
     ]
    }
   ],
   "source": [
    "import ee\n",
    "import geemap\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "img = ee.Image('LANDSAT/LC08/C01/T1_SR/LC08_038029_20180810') \\\n",
    "  .select(['B4', 'B5', 'B6'])\n",
    "\n",
    "aoi = ee.Geometry.Polygon(\n",
    "  [[[-110.8, 44.7],\n",
    "    [-110.8, 44.6],\n",
    "    [-110.6, 44.6],\n",
    "    [-110.6, 44.7]]], None, False)\n",
    "\n",
    "rgb_img = geemap.ee_to_numpy(img, region=aoi)\n",
    "print(rgb_img.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scale the data to [0, 255] to show as an RGB image. \n",
    "# Adapted from https://bit.ly/2XlmQY8. Credits to Justin Braaten\n",
    "rgb_img_test = (255*((rgb_img[:, :, 0:3] - 100)/3500)).astype('uint8')\n",
    "plt.imshow(rgb_img_test)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create an interactive map "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map = geemap.Map(center=(40, -100), zoom=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3ff40840fa8748d683d6377e02a72520",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[40, -100], controls=(WidgetControl(options=['position'], widget=HBox(children=(ToggleButton(value=…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Add Earth Engine dataset\n",
    "dem = ee.Image('USGS/SRTMGL1_003')\n",
    "landcover = ee.Image(\"ESA/GLOBCOVER_L4_200901_200912_V2_3\").select('landcover')\n",
    "landsat7 = ee.Image('LE7_TOA_5YEAR/1999_2003')\n",
    "states = ee.FeatureCollection(\"TIGER/2018/States\")\n",
    "\n",
    "# Set visualization parameters.\n",
    "vis_params = {\n",
    "  'min': 0,\n",
    "  'max': 4000,\n",
    "  'palette': ['006633', 'E5FFCC', '662A00', 'D8D8D8', 'F5F5F5']}\n",
    "\n",
    "# Add Earth Eninge layers to Map\n",
    "Map.addLayer(dem, vis_params, 'STRM DEM', True, 0.5)\n",
    "Map.addLayer(landcover, {}, 'Land cover')\n",
    "Map.addLayer(landsat7, {'bands': ['B4', 'B3', 'B2'], 'min': 20, 'max': 200}, 'Landsat 7')\n",
    "Map.addLayer(states, {}, \"US States\")\n",
    "\n",
    "Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split panel map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map = geemap.Map()\n",
    "landsat7 = ee.Image('LE7_TOA_5YEAR/1999_2003') \\\n",
    "    .select([0, 1, 2, 3, 4, 6])\n",
    "landsat_vis = {\n",
    "    'bands': ['B4', 'B3', 'B2'], \n",
    "    'gamma': 1.4\n",
    "}\n",
    "Map.addLayer(landsat7, landsat_vis, \"LE7_TOA_5YEAR/1999_2003\")\n",
    "\n",
    "hyperion = ee.ImageCollection('EO1/HYPERION') \\\n",
    "    .filter(ee.Filter.date('2016-01-01', '2017-03-01'));\n",
    "hyperion_vis = {\n",
    "  'min': 1000.0,\n",
    "  'max': 14000.0,\n",
    "  'gamma': 2.5,\n",
    "}\n",
    "Map.addLayer(hyperion, hyperion_vis, 'EO1/HYPERION');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map.set_plot_options(plot_type='bar', add_marker_cluster=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7600ffd4e90040fd8ead1eb15edf18fe",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[40, -100], controls=(WidgetControl(options=['position'], widget=HBox(children=(ToggleButton(value=…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m = geemap.Map()\n",
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Element.toDictionary: Parameter 'element' is required.\n"
     ]
    }
   ],
   "source": [
    "m.plot_demo()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create_landsat_timelapse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2a63114334c147ddabb8c96388276cbe",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[40, -100], controls=(WidgetControl(options=['position'], widget=HBox(children=(ToggleButton(value=…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Map = geemap.Map()\n",
    "Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "out_dir = os.path.join(os.path.expanduser(\"~\"), 'Downloads')\n",
    "if not os.path.exists(out_dir):\n",
    "    os.makedirs(out_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generating URL...\n",
      "Downloading GIF image from https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/videoThumbnails/79e6ab8e8a6868e7219ceac883153782-a417d53baf7f7cae0fddfbb53b52182d:getPixels\n",
      "Please wait ...\n",
      "The GIF image has been saved to: /home/manmeet/Downloads/landsat_ts_ydm.gif\n",
      "Adding animated text to GIF ...\n",
      "Adding GIF to the map ...\n",
      "The timelapse has been added to the map.\n"
     ]
    }
   ],
   "source": [
    "label = 'Urban Growth in Las Vegas'\n",
    "Map.add_landsat_ts_gif(label=label, start_year=1985, bands=['Red', 'Green', 'Blue'], font_color='white', frames_per_second=10, progress_bar_color='blue')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import ee\n",
    "import geemap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "feb8090d12c44e9793514b776a73a0b9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[40, -100], controls=(WidgetControl(options=['position'], widget=HBox(children=(ToggleButton(value=…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Map = geemap.Map()\n",
    "Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "roi = ee.Geometry.Polygon(\n",
    "    [[[-115.471773, 35.892718],\n",
    "      [-115.471773, 36.409454],\n",
    "        [-114.271283, 36.409454],\n",
    "        [-114.271283, 35.892718],\n",
    "        [-115.471773, 35.892718]]], None, False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "collection = geemap.landsat_timeseries(roi=roi, start_year=1985, end_year=2019, start_date='06-10', end_date='09-20')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "35\n"
     ]
    }
   ],
   "source": [
    "print(collection.size().getInfo())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "first_image = collection.first()\n",
    "\n",
    "vis = {\n",
    "    'bands': ['NIR', 'Red', 'Green'],\n",
    "    'min': 0,\n",
    "    'max': 4000,\n",
    "    'gamma': [1, 1, 1]\n",
    "}\n",
    "\n",
    "Map.addLayer(first_image, vis, 'First image')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define arguments for animation function parameters.\n",
    "video_args = {\n",
    "  'dimensions': 768,\n",
    "  'region': roi,\n",
    "  'framesPerSecond': 10,\n",
    "  'bands': ['NIR', 'Red', 'Green'],\n",
    "  'min': 0,\n",
    "  'max': 4000,\n",
    "  'gamma': [1, 1, 1]\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "work_dir = os.path.join(os.path.expanduser(\"~\"), 'Downloads')\n",
    "if not os.path.exists(work_dir):\n",
    "    os.makedirs(work_dir)\n",
    "out_gif = os.path.join(work_dir, \"landsat_ts.gif\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generating URL...\n",
      "Downloading GIF image from https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/videoThumbnails/975610d800c2673e301aad4656ef71c6-0b21fc73eb831a4b16f22a13176385ba:getPixels\n",
      "Please wait ...\n",
      "The GIF image has been saved to: /home/manmeet/Downloads/landsat_ts.gif\n"
     ]
    }
   ],
   "source": [
    "geemap.download_ee_video(collection, video_args, out_gif)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add animated text to GIF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8e8c392668ec472ca01c82bbf8d7d5cd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "geemap.show_image(out_gif)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "texted_gif = os.path.join(work_dir, \"landsat_ts_text.gif\")\n",
    "geemap.add_text_to_gif(out_gif, texted_gif, xy=('3%', '5%'), text_sequence=1985, font_size=30, font_color='#ffffff', add_progress_bar=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "label = 'Urban Growth in Las Vegas'\n",
    "geemap.add_text_to_gif(texted_gif, texted_gif, xy=('2%', '88%'), text_sequence=label, font_size=30, font_color='#ffffff', progress_bar_color='cyan')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "251505f8e9af437ea1a390452a9c2edc",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "geemap.show_image(texted_gif)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "NAIP: National Agriculture Imagery Program\n",
    "The National Agriculture Imagery Program (NAIP) acquires aerial imagery during the agricultural growing seasons in the continental U.S.\n",
    "\n",
    "NAIP projects are contracted each year based upon available funding and the FSA imagery acquisition cycle. Beginning in 2003, NAIP was acquired on a 5-year cycle. 2008 was a transition year, and a three-year cycle began in 2009.\n",
    "\n",
    "NAIP imagery is acquired at a one-meter ground sample distance (GSD) with a horizontal accuracy that matches within six meters of photo-identifiable ground control points, which are used during image inspection.\n",
    "\n",
    "Older images were collected using 3 bands (Red, Green, and Blue: RGB), but newer imagery is usually collected with an additional near-infrared band (RGBN).\n",
    "\n",
    "More information about NAIP imagery can be found on Earth Engine Data Catalog."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create annual composite of NAIP imagery\n",
    "Select 4-band (RGBN) NAIP imagery."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map = geemap.Map()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "naip_ts = geemap.naip_timeseries(start_year=2009, end_year=2018)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a list of layer names to be shown under the dropdown list."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['NAIP 2009', 'NAIP 2010', 'NAIP 2011', 'NAIP 2012', 'NAIP 2013', 'NAIP 2014', 'NAIP 2015', 'NAIP 2016', 'NAIP 2017', 'NAIP 2018']\n"
     ]
    }
   ],
   "source": [
    "layer_names = ['NAIP ' + str(year) for year in range(2009, 2019)]\n",
    "print(layer_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set visualization parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "naip_vis = {'bands': ['N', 'R', 'G']}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a split-panel map for visualizing NAIP imagery"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7c8650a7da534ba988f300b1ecbe3af5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[40, -100], controls=(WidgetControl(options=['position'], widget=Dropdown(layout=Layout(max_width='…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Map = geemap.Map()\n",
    "Map.ts_inspector(left_ts=naip_ts, right_ts=naip_ts, left_names=layer_names, right_names=layer_names, left_vis=naip_vis, right_vis=naip_vis)\n",
    "Map"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Create annual composite of Landsat imagery\n",
    "Use the drawing tools to create an ROI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ee\n",
    "import geemap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3c11417c7c944509a7f15b2277083456",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[40, -100], controls=(WidgetControl(options=['position'], widget=HBox(children=(ToggleButton(value=…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Map = geemap.Map()\n",
    "Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "region = Map.draw_last_feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "if region is not None:\n",
    "    roi = region.geometry()\n",
    "else: \n",
    "    roi = ee.Geometry.Polygon(\n",
    "        [[[-115.897448, 35.640766], \n",
    "          [-115.897448, 36.603608], \n",
    "          [-113.784915, 36.603608], \n",
    "          [-113.784915, 35.640766], \n",
    "          [-115.897448, 35.640766]]], None, False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'geodesic': False, 'type': 'Polygon', 'coordinates': [[[-115.897448, 35.640766], [-115.897448, 36.603608], [-113.784915, 36.603608], [-113.784915, 35.640766], [-115.897448, 35.640766]]]}\n"
     ]
    }
   ],
   "source": [
    "print(roi.getInfo())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "landsat_ts = geemap.landsat_timeseries(roi=roi, start_year=1984, end_year=2019, start_date='01-01', end_date='12-31')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Landsat 1984', 'Landsat 1985', 'Landsat 1986', 'Landsat 1987', 'Landsat 1988', 'Landsat 1989', 'Landsat 1990', 'Landsat 1991', 'Landsat 1992', 'Landsat 1993', 'Landsat 1994', 'Landsat 1995', 'Landsat 1996', 'Landsat 1997', 'Landsat 1998', 'Landsat 1999', 'Landsat 2000', 'Landsat 2001', 'Landsat 2002', 'Landsat 2003', 'Landsat 2004', 'Landsat 2005', 'Landsat 2006', 'Landsat 2007', 'Landsat 2008', 'Landsat 2009', 'Landsat 2010', 'Landsat 2011', 'Landsat 2012', 'Landsat 2013', 'Landsat 2014', 'Landsat 2015', 'Landsat 2016', 'Landsat 2017', 'Landsat 2018', 'Landsat 2019']\n"
     ]
    }
   ],
   "source": [
    "layer_names = ['Landsat ' + str(year) for year in range(1984, 2020)]\n",
    "print(layer_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "landsat_vis = {\n",
    "    'min': 0,\n",
    "    'max': 4000,\n",
    "    'gamma': [1, 1, 1],\n",
    "    'bands': ['NIR', 'Red', 'Green']}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "75f91842f3c74067b10a26a5d0461315",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[36.12274913882652, -114.84118150000003], controls=(WidgetControl(options=['position'], widget=Drop…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Map = geemap.Map()\n",
    "Map.ts_inspector(left_ts=landsat_ts, right_ts=landsat_ts, left_names=layer_names, right_names=layer_names, left_vis=landsat_vis, right_vis=landsat_vis)\n",
    "Map.centerObject(roi, zoom=8)\n",
    "Map"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Compare Landsat imagery and National Land Cover Database (NLCD)\n",
    "More information about NLCD can be found at the Earth Engine Data Catalog."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ee\n",
    "import geemap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "eab89c5c871146218de45b447593243e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[40, -100], controls=(WidgetControl(options=['position'], widget=HBox(children=(ToggleButton(value=…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Map = geemap.Map()\n",
    "Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "NLCD = ee.ImageCollection('USGS/NLCD')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['USGS/NLCD/NLCD1992', 'USGS/NLCD/NLCD2001', 'USGS/NLCD/NLCD2001_AK', 'USGS/NLCD/NLCD2001_HI', 'USGS/NLCD/NLCD2001_PR', 'USGS/NLCD/NLCD2004', 'USGS/NLCD/NLCD2006', 'USGS/NLCD/NLCD2008', 'USGS/NLCD/NLCD2011', 'USGS/NLCD/NLCD2011_AK', 'USGS/NLCD/NLCD2011_HI', 'USGS/NLCD/NLCD2011_PR', 'USGS/NLCD/NLCD2013', 'USGS/NLCD/NLCD2016']\n"
     ]
    }
   ],
   "source": [
    "NLCD_layers = NLCD.aggregate_array('system:id').getInfo()\n",
    "print(NLCD_layers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "NLCD2001 = ee.Image('USGS/NLCD/NLCD2001').select('landcover')\n",
    "NLCD2006 = ee.Image('USGS/NLCD/NLCD2006').select('landcover')\n",
    "NLCD2011 = ee.Image('USGS/NLCD/NLCD2011').select('landcover')\n",
    "NLCD2016 = ee.Image('USGS/NLCD/NLCD2016').select('landcover')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "NLCD = ee.ImageCollection([NLCD2001, NLCD2006, NLCD2011, NLCD2016])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['NLCD 2001', 'NLCD 2006', 'NLCD 2011', 'NLCD 2016']\n"
     ]
    }
   ],
   "source": [
    "NLCD_layer_names = ['NLCD ' + str(year) for year in range(2001, 2017, 5)]\n",
    "print(NLCD_layer_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "roi = ee.Geometry.Polygon(\n",
    "    [[[-115.897448, 35.640766], \n",
    "      [-115.897448, 36.603608], \n",
    "      [-113.784915, 36.603608], \n",
    "      [-113.784915, 35.640766], \n",
    "      [-115.897448, 35.640766]]], None, False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "landsat_ts = geemap.landsat_timeseries(roi=roi, start_year=2001, end_year=2016, start_date='01-01', end_date='12-31')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "landsat_layer_names = ['Landsat ' + str(year) for year in range(2001, 2017)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "landsat_vis = {\n",
    "    'min': 0,\n",
    "    'max': 4000,\n",
    "    'gamma': [1, 1, 1],\n",
    "    'bands': ['NIR', 'Red', 'Green']}\n",
    "\n",
    "nlcd_vis = {\n",
    "    'bands': ['landcover']\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ff0c4efed8164924bd7e535c2352b709",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[36.12274913882652, -114.84118150000003], controls=(WidgetControl(options=['position'], widget=Drop…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Map = geemap.Map()\n",
    "Map.ts_inspector(left_ts=landsat_ts, right_ts=NLCD, left_names=landsat_layer_names, right_names=NLCD_layer_names, left_vis=landsat_vis, right_vis=nlcd_vis)\n",
    "Map.centerObject(roi, zoom=8)\n",
    "Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ee\n",
    "import geemap"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Create an interactive map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3ae31d85ff214592a14b0bf721862128",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[40, -100], controls=(WidgetControl(options=['position'], widget=HBox(children=(ToggleButton(value=…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Map = geemap.Map(toolbar_ctrl=True)\n",
    "Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add Earth Engine dataset\n",
    "dem = ee.Image('USGS/SRTMGL1_003')\n",
    "landcover = ee.Image(\"ESA/GLOBCOVER_L4_200901_200912_V2_3\").select('landcover')\n",
    "landsat7 = ee.Image('LE7_TOA_5YEAR/1999_2003')\n",
    "states = ee.FeatureCollection(\"TIGER/2018/States\")\n",
    "\n",
    "# Set visualization parameters.\n",
    "vis_params = {\n",
    "  'min': 0,\n",
    "  'max': 4000,\n",
    "  'palette': ['006633', 'E5FFCC', '662A00', 'D8D8D8', 'F5F5F5']}\n",
    "\n",
    "# Add Earth Eninge layers to Map\n",
    "Map.addLayer(dem, vis_params, 'STRM DEM', True, 0.5)\n",
    "Map.addLayer(landcover, {}, 'Land cover')\n",
    "Map.addLayer(landsat7, {'bands': ['B4', 'B3', 'B2'], 'min': 20, 'max': 200}, 'Landsat 7')\n",
    "Map.addLayer(states, {}, \"US States\")"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Exporting maps as HTML\n",
    "You can either click the camera icon on toolbar to export maps or use the following script."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "download_dir = os.path.join(os.path.expanduser('~'), 'Downloads')\n",
    "if not os.path.exists(download_dir):\n",
    "    os.makedirs(download_dir)\n",
    "html_file = os.path.join(download_dir, 'my_map.html')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map.to_html(outfile=html_file, title='My Map', width='100%', height='880px')"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Exporting maps as PNG/JPG\n",
    "Make sure you click the fullscreen button on the map to maximum the map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "png_file = os.path.join(download_dir, 'my_map.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map.to_image(outfile=png_file, monitor=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "jpg_file = os.path.join(download_dir, 'my_map.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map.to_image(outfile=jpg_file, monitor=1)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "publish maps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ee \n",
    "import geemap.eefolium as geemap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a map centered at (lat, lon).\n",
    "Map = geemap.Map(center=[40, -100], zoom=4)\n",
    "\n",
    "# Use an elevation dataset and terrain functions to create\n",
    "# a custom visualization of topography.\n",
    "\n",
    "# Load a global elevation image.\n",
    "elev = ee.Image('USGS/GMTED2010')\n",
    "\n",
    "# Zoom to an area of interest.\n",
    "Map.setCenter(-121.069, 50.709, 6)\n",
    "\n",
    "# Add the elevation to the map.\n",
    "Map.addLayer(elev, {}, 'elev')\n",
    "\n",
    "# Use the terrain algorithms to compute a hillshade with 8-bit values.\n",
    "shade = ee.Terrain.hillshade(elev)\n",
    "Map.addLayer(shade, {}, 'hillshade', False)\n",
    "\n",
    "# Create a \"sea\" variable to be used for cartographic purposes\n",
    "sea = elev.lte(0)\n",
    "Map.addLayer(sea.mask(sea), {'palette':'000022'}, 'sea', False)\n",
    "\n",
    "# Create a custom elevation palette from hex strings.\n",
    "elevationPalette = ['006600', '002200', 'fff700', 'ab7634', 'c4d0ff', 'ffffff']\n",
    "# Use these visualization parameters, customized by location.\n",
    "visParams = {'min': 1, 'max': 3000, 'palette': elevationPalette}\n",
    "\n",
    "# Create a mosaic of the sea and the elevation data\n",
    "visualized = ee.ImageCollection([\n",
    "  # Mask the elevation to get only land\n",
    "  elev.mask(sea.Not()).visualize(**visParams),\n",
    "  # Use the sea mask directly to display sea.\n",
    "  sea.mask(sea).visualize(**{'palette':'000022'})\n",
    "]).mosaic()\n",
    "\n",
    "# Note that the visualization image doesn't require visualization parameters.\n",
    "Map.addLayer(visualized, {}, 'elev palette', False)\n",
    "\n",
    "# Convert the visualized elevation to HSV, first converting to [0, 1] data.\n",
    "hsv = visualized.divide(255).rgbToHsv()\n",
    "# Select only the hue and saturation bands.\n",
    "hs = hsv.select(0, 1)\n",
    "# Convert the hillshade to [0, 1] data, as expected by the HSV algorithm.\n",
    "v = shade.divide(255)\n",
    "# Create a visualization image by converting back to RGB from HSV.\n",
    "# Note the cast to byte in order to export the image correctly.\n",
    "rgb = hs.addBands(v).hsvToRgb().multiply(255).byte()\n",
    "Map.addLayer(rgb, {}, 'styled')\n",
    "\n",
    "states = ee.FeatureCollection('TIGER/2018/States')\n",
    "Map.addLayer(ee.Image().paint(states, 0, 2), {}, \"US States\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
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                function latLngPop(e) {
                    lat_lng_popup_99ea46e4c2074f30883bc8548df0749b
                        .setLatLng(e.latlng)
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</script> onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<geemap.eefolium.Map at 0x7fd015713e48>"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Add layer control to the map.\n",
    "Map.setControlVisibility()\n",
    "# Display the map.\n",
    "Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Publishing report and associated data - please wait..\n",
      "Report successfully published at https://datapane.com/u/manmeet3591/reports/gee-folium-map/\n"
     ]
    }
   ],
   "source": [
    "Map.publish(name='gee_folium_map', headline='Terrain Visualization', visibility='PUBLIC', overwrite=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Netcdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geemap\n",
    "import os\n",
    "import xarray as xr\n",
    "from ipyleaflet import Map, TileLayer, basemaps\n",
    "from ipyleaflet.velocity import Velocity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "model_id": "30ba39b60c854ff8a4bbbc00a1ecd553",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[44.33, -130.6], controls=(WidgetControl(options=['position'], widget=HBox(children=(ToggleButton(v…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Map = geemap.Map(center=[44.33, -130.60], zoom=3, interpolation='nearest')\n",
    "Map.add_layer(basemaps.CartoDB.DarkMatter)\n",
    "Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path = os.path.abspath('/home/manmeet/Documents/gee_lockdown/wind-global.nc')\n",
    "if not os.path.exists(file_path):\n",
    "    url = 'https://github.com/giswqs/geemap/raw/master/examples/data/wind-global.nc'\n",
    "    import requests\n",
    "    r = requests.get(url)\n",
    "    wind_data = r.content\n",
    "    with open(file_path, 'wb') as f:\n",
    "        f.write(wind_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
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       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lat: 181, lon: 360)\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 90.0 89.0 88.0 87.0 86.0 ... -87.0 -88.0 -89.0 -90.0\n",
       "  * lon      (lon) float64 0.0 1.0 2.0 3.0 4.0 ... 355.0 356.0 357.0 358.0 359.0\n",
       "Data variables:\n",
       "    u_wind   (lat, lon) float64 4.54 4.52 4.49 4.47 ... -2.97 -2.92 -2.86 -2.8\n",
       "    v_wind   (lat, lon) float64 -1.36 -1.44 -1.52 -1.6 ... -3.17 -3.22 -3.27\n",
       "Attributes:\n",
       "    centerName:      US National Weather Service - NCEP(WMC)\n",
       "    disciplineName:  Meteorological products\n",
       "    refTime:         2016-04-30T06:00:00.000Z</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-2c007259-a8fe-46b8-ac4b-b8bf0fbd26c6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2c007259-a8fe-46b8-ac4b-b8bf0fbd26c6' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 181</li><li><span class='xr-has-index'>lon</span>: 360</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-be3c2f84-a9f0-4cc2-8542-d331f175059b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-be3c2f84-a9f0-4cc2-8542-d331f175059b' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.0 89.0 88.0 ... -89.0 -90.0</div><input id='attrs-5aac97e3-ea05-47b1-9b88-1ee78fa2b5e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5aac97e3-ea05-47b1-9b88-1ee78fa2b5e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c4f0f2a-c7c8-4cb1-98a4-4ebdbb26f47d' class='xr-var-data-in' type='checkbox'><label for='data-4c4f0f2a-c7c8-4cb1-98a4-4ebdbb26f47d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 90.,  89.,  88.,  87.,  86.,  85.,  84.,  83.,  82.,  81.,  80.,  79.,\n",
       "        78.,  77.,  76.,  75.,  74.,  73.,  72.,  71.,  70.,  69.,  68.,  67.,\n",
       "        66.,  65.,  64.,  63.,  62.,  61.,  60.,  59.,  58.,  57.,  56.,  55.,\n",
       "        54.,  53.,  52.,  51.,  50.,  49.,  48.,  47.,  46.,  45.,  44.,  43.,\n",
       "        42.,  41.,  40.,  39.,  38.,  37.,  36.,  35.,  34.,  33.,  32.,  31.,\n",
       "        30.,  29.,  28.,  27.,  26.,  25.,  24.,  23.,  22.,  21.,  20.,  19.,\n",
       "        18.,  17.,  16.,  15.,  14.,  13.,  12.,  11.,  10.,   9.,   8.,   7.,\n",
       "         6.,   5.,   4.,   3.,   2.,   1.,   0.,  -1.,  -2.,  -3.,  -4.,  -5.,\n",
       "        -6.,  -7.,  -8.,  -9., -10., -11., -12., -13., -14., -15., -16., -17.,\n",
       "       -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29.,\n",
       "       -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41.,\n",
       "       -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53.,\n",
       "       -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65.,\n",
       "       -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77.,\n",
       "       -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89.,\n",
       "       -90.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0 ... 357.0 358.0 359.0</div><input id='attrs-a12313fa-b15e-44c2-a410-c1bf0f27283e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a12313fa-b15e-44c2-a410-c1bf0f27283e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1510dc7d-9f2f-4ff3-a343-f253f22a39d0' class='xr-var-data-in' type='checkbox'><label for='data-1510dc7d-9f2f-4ff3-a343-f253f22a39d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0.,   1.,   2., ..., 357., 358., 359.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e42387d7-dcc6-4fdb-ab5e-843208da91ce' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e42387d7-dcc6-4fdb-ab5e-843208da91ce' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>u_wind</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1b30e817-4b76-4a85-9f25-c991a0ffe5a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1b30e817-4b76-4a85-9f25-c991a0ffe5a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-929cda84-7b5f-40fd-9cec-be632f11cd2a' class='xr-var-data-in' type='checkbox'><label for='data-929cda84-7b5f-40fd-9cec-be632f11cd2a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 4.54,  4.52,  4.49, ...,  4.61,  4.59,  4.57],\n",
       "       [ 3.51,  3.5 ,  3.5 , ...,  3.5 ,  3.5 ,  3.5 ],\n",
       "       [ 1.62,  1.67,  1.73, ...,  1.45,  1.51,  1.56],\n",
       "       ...,\n",
       "       [-3.22, -3.1 , -2.99, ..., -3.58, -3.46, -3.34],\n",
       "       [-4.53, -4.46, -4.4 , ..., -4.69, -4.64, -4.58],\n",
       "       [-2.75, -2.69, -2.63, ..., -2.92, -2.86, -2.8 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_wind</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e44222e3-34c6-4092-9695-e20acf68fbb1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e44222e3-34c6-4092-9695-e20acf68fbb1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91109802-6b77-4960-b5ca-62d0887cbc48' class='xr-var-data-in' type='checkbox'><label for='data-91109802-6b77-4960-b5ca-62d0887cbc48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-1.36, -1.44, -1.52, ..., -1.13, -1.21, -1.29],\n",
       "       [-1.16, -1.2 , -1.25, ..., -1.02, -1.06, -1.11],\n",
       "       [-0.91, -0.93, -0.96, ..., -0.84, -0.86, -0.88],\n",
       "       ...,\n",
       "       [-4.75, -4.8 , -4.85, ..., -4.57, -4.63, -4.69],\n",
       "       [-3.92, -4.03, -4.15, ..., -3.58, -3.7 , -3.81],\n",
       "       [-3.32, -3.37, -3.41, ..., -3.17, -3.22, -3.27]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e934187e-2f28-47f1-9726-a57c1d1e98bd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e934187e-2f28-47f1-9726-a57c1d1e98bd' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>centerName :</span></dt><dd>US National Weather Service - NCEP(WMC)</dd><dt><span>disciplineName :</span></dt><dd>Meteorological products</dd><dt><span>refTime :</span></dt><dd>2016-04-30T06:00:00.000Z</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lat: 181, lon: 360)\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 90.0 89.0 88.0 87.0 86.0 ... -87.0 -88.0 -89.0 -90.0\n",
       "  * lon      (lon) float64 0.0 1.0 2.0 3.0 4.0 ... 355.0 356.0 357.0 358.0 359.0\n",
       "Data variables:\n",
       "    u_wind   (lat, lon) float64 ...\n",
       "    v_wind   (lat, lon) float64 ...\n",
       "Attributes:\n",
       "    centerName:      US National Weather Service - NCEP(WMC)\n",
       "    disciplineName:  Meteorological products\n",
       "    refTime:         2016-04-30T06:00:00.000Z"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = xr.open_dataset(file_path)\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "30ba39b60c854ff8a4bbbc00a1ecd553",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(bottom=1017.0, center=[44.33, -130.6], controls=(WidgetControl(options=['position'], widget=HBox(children=…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_options = {\n",
    "    'velocityType': 'Global Wind',\n",
    "    'displayPosition': 'bottomleft',\n",
    "    'displayEmptyString': 'No wind data'\n",
    "}\n",
    "wind = Velocity(\n",
    "    data=ds, \n",
    "    name = 'Velocity',\n",
    "    zonal_speed='u_wind', meridional_speed='v_wind', \n",
    "    latitude_dimension='lat', longitude_dimension='lon', \n",
    "    velocity_scale=0.01, max_velocity=20, \n",
    "    display_options=display_options\n",
    ")\n",
    "Map.add_layer(wind)\n",
    "Map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Oil palm concessions in southern Myanmar consist mostly of unconverted forest\n",
    "Credits to Keiko Nomura\n",
    "\n",
    "GEE App: https://nkeikon.users.earthengine.app/view/tanintharyi-oil-palm-and-rubber-map\n",
    "\n",
    "Source code: https://github.com/nkeikon/tanintharyi\n",
    "\n",
    "Reference: https://go.nature.com/2QBIrYe\n",
    "\n",
    "Demo: https://i.imgur.com/VrYKmVG.gifv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Installs geemap package\n",
    "import subprocess\n",
    "\n",
    "try:\n",
    "    import geemap\n",
    "except ImportError:\n",
    "    print('geemap package not installed. Installing ...')\n",
    "    subprocess.check_call([\"python\", '-m', 'pip', 'install', 'geemap'])\n",
    "    import geemap\n",
    "\n",
    "\n",
    "# Authenticates and initializes Earth Engine\n",
    "import ee\n",
    "\n",
    "try:\n",
    "    ee.Initialize()\n",
    "except Exception as e:\n",
    "    ee.Authenticate()\n",
    "    ee.Initialize()\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Create an interactive map\n",
    "The default basemap is Google Satellite. Additional basemaps can be added using the Map.add_basemap() function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "layer already on map: TileLayer(attribution='Google', name='Google Maps', options=['attribution', 'detect_retina', 'max_native_zoom', 'max_zoom', 'min_native_zoom', 'min_zoom', 'no_wrap', 'tile_size', 'tms'], url='https://mt1.google.com/vt/lyrs=m&x={x}&y={y}&z={z}')\n",
      "Basemap can only be one of the following:\n",
      "  ROADMAP\n",
      "  SATELLITE\n",
      "  TERRAIN\n",
      "  HYBRID\n",
      "  ESRI\n",
      "  Esri Ocean\n",
      "  Esri Satellite\n",
      "  Esri Standard\n",
      "  Esri Terrain\n",
      "  Esri Transportation\n",
      "  Esri Topo World\n",
      "  Esri National Geographic\n",
      "  Esri Shaded Relief\n",
      "  Esri Physical Map\n",
      "  FWS NWI Wetlands\n",
      "  FWS NWI Wetlands Raster\n",
      "  Google Maps\n",
      "  Google Satellite\n",
      "  Google Terrain\n",
      "  Google Satellite Hybrid\n",
      "  NLCD 2016 CONUS Land Cover\n",
      "  NLCD 2013 CONUS Land Cover\n",
      "  NLCD 2011 CONUS Land Cover\n",
      "  NLCD 2008 CONUS Land Cover\n",
      "  NLCD 2006 CONUS Land Cover\n",
      "  NLCD 2004 CONUS Land Cover\n",
      "  NLCD 2001 CONUS Land Cover\n",
      "  USGS NAIP Imagery\n",
      "  USGS Hydrography\n",
      "  USGS 3DEP Elevation\n",
      "  OpenStreetMap.Mapnik\n",
      "  OpenStreetMap.BlackAndWhite\n",
      "  OpenStreetMap.DE\n",
      "  OpenStreetMap.France\n",
      "  OpenStreetMap.HOT\n",
      "  OpenTopoMap\n",
      "  Hydda.Full\n",
      "  Hydda.Base\n",
      "  Esri.WorldStreetMap\n",
      "  Esri.DeLorme\n",
      "  Esri.WorldTopoMap\n",
      "  Esri.WorldImagery\n",
      "  Esri.NatGeoWorldMap\n",
      "  HikeBike.HikeBike\n",
      "  MtbMap\n",
      "  CartoDB.Positron\n",
      "  CartoDB.DarkMatter\n",
      "  NASAGIBS.ModisTerraTrueColorCR\n",
      "  NASAGIBS.ModisTerraBands367CR\n",
      "  NASAGIBS.ModisTerraBands721CR\n",
      "  NASAGIBS.ModisAquaTrueColorCR\n",
      "  NASAGIBS.ModisAquaBands721CR\n",
      "  NASAGIBS.ViirsTrueColorCR\n",
      "  NASAGIBS.ViirsEarthAtNight2012\n",
      "  NASAGIBS.BlueMarble3413\n",
      "  NASAGIBS.BlueMarble3031\n",
      "  NASAGIBS.BlueMarble\n",
      "  Strava.All\n",
      "  Strava.Ride\n",
      "  Strava.Run\n",
      "  Strava.Water\n",
      "  Strava.Winter\n",
      "  Stamen.Terrain\n",
      "  Stamen.Toner\n",
      "  Stamen.Watercolor\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "125cc1c0561c4467994c7b5e6e7f9a91",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[40, -100], controls=(WidgetControl(options=['position'], widget=HBox(children=(ToggleButton(value=…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Map = geemap.Map(center=[40,-100], zoom=4)\n",
    "Map.add_basemap('ROADMAP') # Add Google Map\n",
    "Map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Add Earth Engine Python script"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Add Earth Engine data\n",
    "area1 = ee.Image(\"users/nkeikon/myanmar_sr/area1_map\")\n",
    "area2 = ee.Image(\"users/nkeikon/myanmar_sr/area2_map\")\n",
    "tanintharyi = ee.FeatureCollection(\"users/nkeikon/myanmar_sr/TNI\")\n",
    "Map.centerObject(tanintharyi,10)\n",
    "total = ee.ImageCollection([area1,area2]).mosaic()\n",
    "palette =['ff0000',# palm  (red)\n",
    "              '9933ff',#rubber  (purple)\n",
    "              '008000',#other trees  (green)\n",
    "              'lime',#shrub (lime)\n",
    "              'yellow',#bare (yellow)\n",
    "              '0000ff',#river (blue)\n",
    "]\n",
    "viz = {'min':1, 'max':6, 'palette':palette}\n",
    "MAIN = 'Default map'\n",
    "OILPALM = 'Oil palm only'\n",
    "RUBBER = 'Rubber only'\n",
    "OILPALM_RUBBER = 'Oil palm and rubber'\n",
    "mainVis = total.visualize(**viz)\n",
    "oilpalmVis = total.eq(1).selfMask().visualize(**{'palette':'red'})\n",
    "rubberVis = total.eq(2).selfMask().visualize(**{'palette':'purple'})\n",
    "oilpalm_rubberVis = oilpalmVis.blend(rubberVis)\n",
    "Map.addLayer(mainVis, {}, 'Land cover')\n",
    "Map.addLayer(oilpalmVis, {}, 'Oil palm only')\n",
    "Map.addLayer(rubberVis, {}, 'Rubber only')\n",
    "Map.addLayer(oilpalm_rubberVis, {}, 'Oil palm and rubber')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add widgets to the map\n",
    "import ipywidgets as widgets\n",
    "from ipyleaflet import WidgetControl\n",
    "legend = widgets.HTML(\n",
    "    value='<img src=\"https://i.imgur.com/Ye2sgan.png\">',\n",
    "    placeholder='Land cover',\n",
    "    descripition='Land cover'\n",
    ")\n",
    "\n",
    "citation = widgets.HTML(\n",
    "    value='Reference: <a href=\"https://go.nature.com/2QBIrYe\">https://go.nature.com/2QBIrYe</a>',\n",
    "    placeholder='Land cover',\n",
    "    descripition='Land cover'\n",
    ")\n",
    "\n",
    "dropdown = widgets.Dropdown(\n",
    "    options=[('Land cover', 1), ('Old palm only', 2), ('Rubber only', 3), ('Oil palm and bubber only', 4), ('Show all layers', 5)],\n",
    "    value=5,\n",
    "    description='Select layer',\n",
    ")\n",
    "\n",
    "legend_control = WidgetControl(widget=legend, position='bottomleft')\n",
    "citation_control = WidgetControl(widget=citation, position='bottomright')\n",
    "dropdown_control = WidgetControl(widget=dropdown, position='topright')\n",
    "\n",
    "all_layers = Map.layers\n",
    "\n",
    "def on_change(change):\n",
    "    if change['type'] == 'change' and change['name'] == 'value':\n",
    "        if change['new'] == 5: \n",
    "            Map.layers = all_layers\n",
    "        else:\n",
    "            Map.layers = Map.layers[:3] \n",
    "            layer_index = change['new'] + 2\n",
    "            Map.add_layer(all_layers[layer_index])\n",
    "\n",
    "dropdown.observe(on_change)\n",
    "\n",
    "Map.add_control(legend_control)\n",
    "Map.add_control(citation_control)\n",
    "Map.add_control(dropdown_control)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "125cc1c0561c4467994c7b5e6e7f9a91",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(bottom=122056.0, center=[12.655743865888127, 98.74687371251025], controls=(WidgetControl(options=['positio…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# US Census data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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