dssg/data-exploration/araria_district.ipynb

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  {
   "source": [
    "# OSM Data Exploration\n",
    "\n",
    "## Extraction of districts from shape files\n",
    "For our experiments we consider two underdeveloped districts Araria, Bihar and Namsai, Arunachal Pradesh, the motivation of this comes from this [dna](https://www.dnaindia.com/india/report-out-of-niti-aayog-s-20-most-underdeveloped-districts-19-are-ruled-by-bjp-or-its-allies-2598984) news article, quoting a Niti Aayog Report. We also consider a developed city Bangalore in the south of India."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from dotenv import load_dotenv\n",
    "load_dotenv()\n",
    "import sys\n",
    "sys.path.insert(0, '../dataio')\n",
    "import osm_data_extraction as ode\n",
    "\n",
    "india_shape = os.environ.get(\"DATA_DIR\") + \"/gadm36_shp/gadm36_IND_2.shp\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd \n",
    "import matplotlib.pyplot as plt \n",
    "%matplotlib inline\n",
    "india_gpd = gpd.read_file(india_shape)\n",
    "india_gpd.plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "araria_gdf = ode.extract_district_dataframe(india_gpd, 'Araria')\n",
    "araria_gdf.plot()"
   ]
  },
  {
   "source": [
    "## Fetch Open Street Map Data within Boundaries as Data Frame\n",
    "We use 'add_basemap' function of contextily to add a background map to our plot and make sure the added basemap has the same co-ordinate system (crs) as the boundary extracted from the shape file."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ode.plot_district_boundary_on_osm_tile(araria_gdf, 10, 1.5, 12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Writes to a geotif file\n",
    "ode.write_district_osm_tile(araria_gdf, \"araria.tif\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ode.plot_district_tif(os.environ.get(\"OSM_DIR\") + \"araria.tif\", 9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(araria_poly, araria_graph) = ode.create_district_knots_and_edges_model(araria_gdf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import osmnx as ox\n",
    "araria_kefig, araria_ax = ox.plot_graph(araria_graph)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#tags = {'amenity':True, 'building':True, 'emergency':True, 'highway':True, 'footway':True, 'landuse': True, 'water': True}\n",
    "araria_osmdf = ode.extract_osm_csv(araria_poly)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "araria_osmdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "araria_osmdf.to_csv(os.environ.get(\"OSM_DIR\") + \"araria_osmdf.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "!python ../apps/download-nightlights.py 'Araria' '2015-01-01' '2015-01-05'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": []
  }
 ]
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