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    "<a href=\"https://githubtocolab.com/giswqs/geemap/blob/master/examples/notebooks/cartoee_quickstart.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\"/></a>\n",
    "\n",
    "Uncomment the following line to install [geemap](https://geemap.org) if needed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "source": [
    "# !pip install geemap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `cartoee` quickstart\n",
    "\n",
    "`cartoee` is a lightweight module to aid in creatig publication quality maps from Earth Engine processing results without having to download data. The `cartoee` package does this by requesting png images from EE results (which are usually good enough for visualization) and `cartopy` is used to create the plots. Utility functions are available to create plot aethetics such as gridlines or color bars."
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "%pylab inline\n",
    "\n",
    "import ee\n",
    "import geemap\n",
    "\n",
    "# import the cartoee functionality from geemap\n",
    "from geemap import cartoee"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map = geemap.Map()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting an image\n",
    "\n",
    "In this first example we will explore the most basic functionality including plotting and image, adding a colorbar, and adding visual aethetic features. Here we will use SRTM data to plot global elevation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get an image\n",
    "srtm = ee.Image(\"CGIAR/SRTM90_V4\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "region = [-180,-60,180,85] # define bounding box to request data\n",
    "vis = {'min':0,'max':3000} # define visualization parameters for image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure(figsize=(10,7))\n",
    "\n",
    "# use cartoee to get a map\n",
    "ax = cartoee.get_map(srtm,region=region,vis_params=vis)\n",
    "\n",
    "# add a colorbar to the map using the visualization params we passed to the map\n",
    "cartoee.add_colorbar(ax, vis, loc=\"bottom\",label=\"Elevation\",orientation=\"horizontal\")\n",
    "\n",
    "# add gridlines to the map at a specified interval\n",
    "cartoee.add_gridlines(ax,interval=[60,30],linestyle=\":\")\n",
    "\n",
    "# add coastlines using the cartopy api\n",
    "ax.coastlines(color=\"red\")\n",
    "\n",
    "show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a decent map for minimal amount of code. But we can also easily use matplotlib colormaps to visualize our EE results to add more color. Here we add a `cmap` keyword to the `.get_map()` and `.add_colorbar()` functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure(figsize=(10,7))\n",
    "\n",
    "cmap = \"gist_earth\" # colormap we want to use\n",
    "\n",
    "# use cartoee to get a map\n",
    "ax = cartoee.get_map(srtm,region=region,vis_params=vis,cmap= cmap)\n",
    "\n",
    "# add a colorbar to the map using the visualization params we passed to the map\n",
    "cartoee.add_colorbar(ax, vis, cmap=cmap, loc=\"bottom\",label=\"Elevation\",orientation=\"horizontal\")\n",
    "\n",
    "# add gridlines to the map at a specified interval\n",
    "cartoee.add_gridlines(ax,interval=[60,30],linestyle=\":\")\n",
    "\n",
    "# add coastlines using the cartopy api\n",
    "ax.coastlines(color=\"red\")\n",
    "\n",
    "show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting an RGB image\n",
    "\n",
    "`cartoee` also allows for plotting of RGB image results directly. Here is an example of plotting a Landsat false-color scene."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get a landsat image to visualize\n",
    "image = ee.Image('LANDSAT/LC08/C01/T1_SR/LC08_044034_20140318')\n",
    "\n",
    "# define the visualization parameters to view\n",
    "vis ={\"bands\": ['B5', 'B4', 'B3'], \"min\": 0, \"max\":5000,\"gamma\":1.3}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# use cartoee to get a map\n",
    "ax = cartoee.get_map(image,vis_params=vis)\n",
    "\n",
    "# pad the view for some visual appeal\n",
    "cartoee.pad_view(ax)\n",
    "\n",
    "# add the gridlines and specify that the xtick labels be rotated 45 degrees\n",
    "cartoee.add_gridlines(ax,interval=0.5,xtick_rotation=45,linestyle=\":\")\n",
    "\n",
    "# add the coastline\n",
    "ax.coastlines(color=\"yellow\")\n",
    "\n",
    "show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By default, if a region is not provided via the `region` keyword the whole extent of the image will be plotted as seen in the previous Landsat example. We can also zoom to a specific region of an image by defining the region to plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# here is the bounding box of the map extent we want to use\n",
    "# formatted a [W,S,E,N]\n",
    "zoom_region = [-122.6265,37.3458,-121.8025, 37.9178]\n",
    "\n",
    "# plot the map over the region of interest\n",
    "ax = cartoee.get_map(image,vis_params=vis,region=zoom_region)\n",
    "\n",
    "# add the gridlines and specify that the xtick labels be rotated 45 degrees\n",
    "cartoee.add_gridlines(ax,interval=0.15,xtick_rotation=45,linestyle=\":\")\n",
    "\n",
    "# add coastline\n",
    "ax.coastlines(color=\"yellow\")\n",
    "\n",
    "show()"
   ]
  }
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