ee_cartopy_polar_coordinate_ndvi.ipynb

ee_cartopy_polar_coordinate_ndvi.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "ee_cartopy_polar_coordinate_ndvi.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/jdbcode/54a387020d32e40b60b025e4aa694e64/ee_cartopy_polar_coordinate_ndvi.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EKTYuJjs2TId"
      },
      "source": [
        "Install conda"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J3GQOPsby4fy"
      },
      "source": [
        "!pip install -q condacolab\n",
        "import condacolab\n",
        "condacolab.install()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pYEeMVFa2YB3"
      },
      "source": [
        "Reload the Colab browser tab (Ctrl + R), then continue with the following code cell to install cartopy via mamba"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dO5I1vtyy61M"
      },
      "source": [
        "!mamba install -c conda-forge -y cartopy=0.19.0"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OClEB5dx2bpd"
      },
      "source": [
        "Earth Engine setup"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xzwb7F_Ty9MM"
      },
      "source": [
        "import ee\n",
        "ee.Authenticate()\n",
        "ee.Initialize()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "I9uU0G6D2g4_"
      },
      "source": [
        "Import packages"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A0Rqc8oky-p0"
      },
      "source": [
        "import cartopy.crs as ccrs\n",
        "import cartopy.feature as cfeature\n",
        "import matplotlib as mpl\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.path as mpath\n",
        "import numpy as np\n",
        "import os\n",
        "import requests"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mBvmJxJy2jFF"
      },
      "source": [
        "Make visualization collection in Earth Engine"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EhSdyqmLzFv8"
      },
      "source": [
        "col = (ee.ImageCollection('MODIS/006/MOD13Q1')\n",
        "           .filterDate('2018-01-01', '2019-01-01'))\n",
        "\n",
        "vis_params = {\n",
        "    'bands': 'NDVI',\n",
        "    'min': -2000,\n",
        "    'max': 8000,\n",
        "    'palette': ['black', 'blanchedalmond', '8FBC8F', '006400'],\n",
        "    'forceRgbOutput': True\n",
        "}\n",
        "\n",
        "aoi = {\n",
        "    'xmin': -180,\n",
        "    'ymin': 60,\n",
        "    'xmax': 180,\n",
        "    'ymax': 90\n",
        "}\n",
        "\n",
        "def vis_rgb(img):\n",
        "    return (img.visualize(**vis_params)\n",
        "                 .unmask(0)\n",
        "                 .set({'date': img.date().format('YYYY-MM-dd')}))\n",
        "\n",
        "col_vis = (col.map(vis_rgb))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yJPbHrBE2oHF"
      },
      "source": [
        "Get thumbnails of the visualization collection downloaded locally"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8-kzRms2zZJG"
      },
      "source": [
        "thumb_params = {\n",
        "  'dimensions': 5000,\n",
        "  'region': ee.Geometry.BBox(aoi['xmin'], aoi['ymin'], aoi['xmax'], aoi['ymax']),\n",
        "  'crs': 'EPSG:4326',\n",
        "  'format': 'PNG'\n",
        "}\n",
        "\n",
        "dates = col_vis.aggregate_array('date').getInfo()\n",
        "\n",
        "frames = []\n",
        "for count, date in enumerate(dates):\n",
        "    img_vis = col_vis.filter(ee.Filter.eq('date', date)).first()\n",
        "    img_url = img_vis.getThumbURL(thumb_params)\n",
        "    img_name = str(count).zfill(3) + '.png'\n",
        "    frames.append(img_name)\n",
        "    print(img_name)\n",
        "    response = requests.get(img_url)\n",
        "    with open(img_name, 'wb') as fd:\n",
        "        fd.write(response.content)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "j8tCsOuo201f"
      },
      "source": [
        "Make a directory to hold altered images"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q5t7GaKazp6k"
      },
      "source": [
        "alt_dir = 'alt'\n",
        "if not os.path.exists(alt_dir):\n",
        "    os.mkdir(alt_dir)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_ehI4XRH23w9"
      },
      "source": [
        "Use cartopy to change the projection of the downloaded images to North Polar Stereo, set the extent of the output plot, and clip by a circle."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CAVq5wBizzRd"
      },
      "source": [
        "def make_plot(frame):\n",
        "    fig = plt.figure(figsize=[8, 8])\n",
        "    ax = plt.axes(projection=ccrs.NorthPolarStereo())\n",
        "    ax.spines['geo'].set_edgecolor('none')\n",
        "    ax.set_extent([aoi['xmin'], aoi['xmax'], aoi['ymin'], aoi['ymax']], ccrs.PlateCarree())\n",
        "    ax.add_feature(cfeature.COASTLINE, edgecolor='grey')\n",
        "    ax.gridlines()\n",
        "\n",
        "    theta = np.linspace(0, 2*np.pi, 100)\n",
        "    center, radius = [0.5, 0.5], 0.5\n",
        "    verts = np.vstack([np.sin(theta), np.cos(theta)]).T\n",
        "    circle = mpath.Path(verts * radius + center)\n",
        "\n",
        "    ax.set_boundary(circle, transform=ax.transAxes)\n",
        "    img = plt.imread(frame)\n",
        "    ax.imshow(img, extent=(aoi['xmin'], aoi['xmax'], aoi['ymin'], aoi['ymax']), origin='upper', transform=ccrs.PlateCarree())\n",
        "    fig.savefig(os.path.join(alt_dir, frame), bbox_inches='tight', pad_inches=0.5, facecolor='grey', edgecolor='none')\n",
        "    plt.close()\n",
        "\n",
        "for frame in frames:\n",
        "    print(frame)\n",
        "    make_plot(frame)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "I0hm72pz3P5g"
      },
      "source": [
        "Make an animation from the frames"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y3Qwwesa0mMk"
      },
      "source": [
        "outfile = 'animation'\n",
        "cmd = 'ffmpeg -framerate 10 -i alt/%03d.png -movflags faststart -pix_fmt yuv420p -vf \"scale=trunc(iw/2)*2:trunc(ih/2)*2\"'\n",
        "\n",
        "cmd_mp4 = f'{cmd} {outfile}.mp4' \n",
        "os.system(cmd_mp4)\n",
        "\n",
        "cmd_gif = f'{cmd} {outfile}.gif' \n",
        "os.system(cmd_gif)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y23_EjqZ497C"
      },
      "source": [
        "Download the MP4 and GIF animations"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pnbo395D8ToS"
      },
      "source": [
        "from google.colab import files\n",
        "files.download(f'{outfile}.mp4')\n",
        "files.download(f'{outfile}.gif') "
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}