cut_alaska_dem.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import salem\n",
    "import matplotlib.pyplot as plt\n",
    "import geopandas as gpd\n",
    "import numpy as np\n",
    "from subprocess import Popen\n",
    "import os\n",
    "from oggm import utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "dem_full = 'Alaska_albers_V3.tif'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Make a shapefile with the tiles in the original projection "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[-1826439.1592820566,\n",
       " 2031800.8407179434,\n",
       " -51.90425149630755,\n",
       " 2664488.0957485037]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = salem.GeoTiff(dem_full)\n",
    "ds.grid.extent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### We make a grid slightly larger so that we can properly divide it in nice boxes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[-1827000.0, 2073000.0, -35000.0, 2665000.0]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid = salem.Grid(x0y0=(-1827000, 2665000), dxdy=(ds.grid.dx, ds.grid.dy), nxny=(130000, 90000), \n",
    "                  proj=ds.grid.proj, pixel_ref='corner')\n",
    "grid = grid.center_grid\n",
    "grid.extent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from math import gcd\n",
    "gcd(grid.nx, grid.ny)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<salem.Grid>\n",
       "  proj: +datum=NAD83 +lat_0=50 +lat_1=55 +lat_2=65 +lon_0=-154 +no_defs+proj=aea +units=m +x_0=0 +y_0=0\n",
       "  pixel_ref: center\n",
       "  origin: upper-left\n",
       "  (nx, ny): (13, 9)\n",
       "  (dx, dy): (300000.0, -300000.0)\n",
       "  (x0, y0): (-1677000.0, 2515000.0)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr_grid = grid.regrid(nx=grid.nx / 10000, ny=grid.ny / 10000)\n",
    "lr_grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "117"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geom = lr_grid.to_geometry()\n",
    "geom['tile'] = ['{:03d}_{:03d}'.format(i, j) for i, j in zip(geom.i, geom.j)]\n",
    "len(geom)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### We keep only the tiles which are relevant to glaciers to save space "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "rgi = gpd.read_file('/home/mowglie/disk/Data/GIS/SHAPES/RGI/RGI_V6/01_rgi60_Alaska/01_rgi60_Alaska.shp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "rgi = rgi.to_crs(geom.crs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "rgi['geometry'] = rgi.buffer(50000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "rgi = rgi.dissolve(by='O1Region')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "rgi.to_file('/home/mowglie/rgibuf_diss.shp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "geom = geom.loc[geom.geometry.intersects(rgi.unary_union)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "geom.plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "geom.to_file('Alaska_albers_V3_tiles.shp')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Apply GDAL "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "37\n",
      "005_001_Alaska_albers_V3\n",
      "006_001_Alaska_albers_V3\n",
      "007_001_Alaska_albers_V3\n",
      "005_002_Alaska_albers_V3\n",
      "006_002_Alaska_albers_V3\n",
      "007_002_Alaska_albers_V3\n",
      "006_003_Alaska_albers_V3\n",
      "007_003_Alaska_albers_V3\n",
      "008_003_Alaska_albers_V3\n",
      "004_004_Alaska_albers_V3\n",
      "005_004_Alaska_albers_V3\n",
      "006_004_Alaska_albers_V3\n",
      "007_004_Alaska_albers_V3\n",
      "008_004_Alaska_albers_V3\n",
      "009_004_Alaska_albers_V3\n",
      "010_004_Alaska_albers_V3\n",
      "011_004_Alaska_albers_V3\n",
      "004_005_Alaska_albers_V3\n",
      "005_005_Alaska_albers_V3\n",
      "006_005_Alaska_albers_V3\n",
      "007_005_Alaska_albers_V3\n",
      "008_005_Alaska_albers_V3\n",
      "009_005_Alaska_albers_V3\n",
      "010_005_Alaska_albers_V3\n",
      "011_005_Alaska_albers_V3\n",
      "003_006_Alaska_albers_V3\n",
      "004_006_Alaska_albers_V3\n",
      "005_006_Alaska_albers_V3\n",
      "006_006_Alaska_albers_V3\n",
      "009_006_Alaska_albers_V3\n",
      "010_006_Alaska_albers_V3\n",
      "011_006_Alaska_albers_V3\n",
      "000_007_Alaska_albers_V3\n",
      "001_007_Alaska_albers_V3\n",
      "002_007_Alaska_albers_V3\n",
      "003_007_Alaska_albers_V3\n",
      "004_007_Alaska_albers_V3\n"
     ]
    }
   ],
   "source": [
    "# read the REMA Tile Index\n",
    "gdf = gpd.read_file('Alaska_albers_V3_tiles.shp') \n",
    "print(len(gdf))\n",
    "\n",
    "full_dir = '/home/mowglie/disk/OGGM_INPUT/download_cache/cluster.klima.uni-bremen.de/'\n",
    "full_dir += '~fmaussion/DEM/Alaska_albers_V3/'\n",
    "utils.mkdir(full_dir, reset=True)\n",
    "\n",
    "for i in range(len(gdf)):\n",
    "    # seperate one tile from the tile index\n",
    "    tile = gdf.iloc[[i]] \n",
    "    \n",
    "    # create one directory for every tile\n",
    "    name = '{}_Alaska_albers_V3'.format(tile.iloc[0].tile)\n",
    "    print(name)\n",
    "    out_dir = os.path.join(full_dir, name)\n",
    "    utils.mkdir(out_dir, reset=True)\n",
    "    \n",
    "    # make and write one shapefile for every tile, necessary for gdalwarp\n",
    "    index_dir = os.path.join(out_dir, 'index')\n",
    "    shp_file = os.path.join(index_dir, name + '_index.shp')\n",
    "    utils.mkdir(index_dir)\n",
    "    tile.to_file(shp_file)\n",
    "    \n",
    "    # name of the GeoTiff tile\n",
    "    dem_tile = os.path.join(out_dir, name + '.tif')\n",
    "\n",
    "    # Use gdalwarp -cutline as shell command to cut one tile at a time\n",
    "    command = 'gdalwarp -cutline {} -crop_to_cutline -of GTiff {} {}'.format(shp_file, dem_full, dem_tile)\n",
    "    p = Popen(command, shell=True)\n",
    "    p.wait()"
   ]
  },
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   "execution_count": null,
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   "outputs": [],
   "source": []
  }
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