xarray-leaflet-geotiff

geotiff.ipynb

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    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "import requests\nimport os\nfrom tqdm import tqdm\nimport numpy as np\nimport zipfile\nimport rioxarray\nimport xarray as xr\nimport xarray_leaflet\nfrom ipyleaflet import Map, basemaps\nfrom matplotlib import pyplot as plt",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "The example SRTM (10 MB) can be downloaded at the link below. Place the downloaded DEM under the same directory of this notebook.\n\nhttps://drive.google.com/file/d/1Cpcpe5XW5Kjfw43vE3aOe5sGSzKYaQRl/view?usp=sharing"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# tif_file = os.path.join(os.getcwd(), 'srtm90.tif')\ntif_file = '/media/hdd/Google-Drive/export/landsat.tif'",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "da = xr.open_rasterio(tif_file)\nda",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "crs = da.rio.crs\nnan = da.attrs['nodatavals'][0]\nda = da.sel(band=[5, 4, 3])\nda = xr.where(da==nan, np.nan, da)\nda = da.rio.write_crs(crs)",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "da",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true,
        "scrolled": false
      },
      "cell_type": "code",
      "source": "# import geemap\n# Map = geemap.Map()\n# Map",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "scrolled": false,
        "trusted": true
      },
      "cell_type": "code",
      "source": "m = Map(center=[40, -100], zoom=4, scroll_wheel_zoom = True)\nm",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "l = da.leaflet.plot(m, x_dim='x', y_dim='y', rgb_dim='band')\nl.interact(opacity=(0.0,1.0,0.1))",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# l = da.leaflet.plot(Map, x_dim='x', y_dim='y', colormap=plt.cm.gray)\n# l.interact(opacity=(0.0,1.0,0.1))",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# import ee",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# image = ee.Image('LANDSAT/LC08/C01/T1_TOA/LC08_044034_20140318').select(['B5', 'B4', 'B3'])",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# geemap.ee_export_image_to_drive(image, 'landsat', scale=90)",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
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      "execution_count": null,
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