SEN_Transport_agriculture-to-road_walking_2021-11-19.ipynb

{
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   "cell_type": "markdown",
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   "source": [
    "# Network analysis in Senegal\n",
    "\n",
    "### Objectives\n",
    "    1)\tUse measures of road-based accessibility to identify road segments that, if rehabilitated, would improve agricultural market activities in Senegal, including during flood conditions.\n",
    "    2)\tGain a better understanding of the accessibility, connectivity, and criticality of roads in Senegal in relationship to agricultural origins, processing & transfer sites, and markets.\n",
    "\n",
    "To this end, the team will develop an accessibility model which measures the travel time from sites of agricultural production to their nearest populated areas, processing centers, and markets. \n",
    "\n",
    "### Datasets for analysis\n",
    "#### ORIGIN\n",
    "    1) agriculture: MapSPAM 2017. Measuring value and potential value. Values might be reassigned to landcover extents (UMD 2019 30m).\n",
    "    2) population: WorldPop 2020, UN-adjusted.\n",
    "    3) settlement extent: GRID3 2020.\n",
    "#### DESTINATION\n",
    "    4) markets: derived from WorldPop 2020 and GRID3 2020 urban clusters.\n",
    "    5) agricultural processing hubs: to be acquired.\n",
    "#### TRAVEL ROUTE\n",
    "    6) roads: OpenStreetMap, July 2021.\n",
    "    7) elevation: \n",
    "#### OBSTACLE\n",
    "    8) flood: FATHOM. 1-in-10, 20, and 50 year flood return periods. \n",
    "#### INTERVENTION\n",
    "    9) upcoming road projects: AGEROUTE interventions separate from the World Bank-financed project\n",
    "    10) targeted road projects: critical road segments identified by this accessibility model's baseline outputs\n",
    "\n",
    "\n",
    "### Model design\n",
    "#### Basic formula: \n",
    "    (a) Off-road driving time from origin to closest road node\n",
    "    +\n",
    "    (b) Driving time from road node in (a) to a destination (closeness measured by road segments speeds)\n",
    "\n",
    "#### Model origin & destination (OD) sets:\n",
    "    A)\tTravel time from an area that has agricultural value/potential to the nearest processing hub (if provided).\n",
    "    B)\tTravel time from an area that has agricultural value/potential to the nearest larger settlement, (“larger” settlement identified using a case-appropriate population metric to be determined).\n",
    "    C)\tTravel time from an area that has agricultural value/potential to the nearest market.\n",
    "    D)\tTravel time from all settlements to the nearest market.\n",
    "    E)\tTravel time from larger settlements to the nearest market.\n",
    "\n",
    "#### Before/after scenarios for each OD set:\n",
    "    1)\tPre-project, baseline weather: No inclement weather. Road network status as of November 2021.\n",
    "    2)\tPre-project, flood: 1-in-10, 1-in-20 and 1-in-50 year flood return period. Road network status as of November 2021.\n",
    "    3)\tPost-project, baseline weather: No inclement weather. Road network status if X number of critical road segments to high-value areas are protected (i.e., their travel times reduced).\n",
    "    4)\tPost-project, flood: 1-in-10 year flood return period. Road network status if X number of critical road segments to high-value areas are protected (i.e., their travel times reduced).\n",
    "\n",
    "#### Notes:\n",
    "    --Destinations are expected to be proximal to the road network, so no measure is taken between road and destination.\n",
    "    --All travel times will be assigned to each model variation’s point of origin; the aggregation up to admin areas is possible if desired.\n",
    "    --Obstacles & interventions modify the road segment speeds. Basic formula is then applied to the modified road network.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prep workspace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\wb527163\\\\GEO-Cdrive-Grace'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os, sys\n",
    "GISFolder = os.getcwd()\n",
    "GISFolder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Note: needed to reinstall rtree due to geopandas import error. Did so in the console. \n",
    "# conda install -c conda-forge rtree=0.9.3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load and filter osm network (step 1)\n",
    "import geopandas as gpd\n",
    "from geopandas import GeoDataFrame\n",
    "import pandas as pd\n",
    "import time\n",
    "sys.path.append(r\"C:\\Users\\wb527163\\.conda\\envs\\geo\\GOSTnets-master\")\n",
    "import GOSTnets as gn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "import osmnx as ox\n",
    "import numpy as np\n",
    "import rasterio as rt\n",
    "import shapely\n",
    "from shapely.geometry import Point, box\n",
    "from shapely.ops import unary_union\n",
    "from shapely.wkt import loads\n",
    "from shapely import wkt\n",
    "from shapely.geometry import LineString, MultiLineString, Point\n",
    "import peartree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#### Might not use these\n",
    "import fiona\n",
    "from osgeo import gdal\n",
    "import importlib\n",
    "import matplotlib.pyplot as plt\n",
    "import subprocess, glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\wb527163\\\\GEO-Cdrive-Grace\\\\SEN-Cdrive'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pth = os.path.join(GISFolder, \"SEN-Cdrive\") # Personal folder system for running model.\n",
    "pth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\wb527163\\\\GEO-Cdrive-Grace\\\\SEN-Cdrive\\\\outputs'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out_pth = os.path.join(GISFolder, \"SEN-Cdrive\\outputs\") # For storing intermediate outputs from the model.\n",
    "out_pth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'R:\\\\SEN\\\\GEO'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "team_pth = 'R:\\\\SEN\\\\GEO' # This is where the unmodified input data is stored. Finalized outputs also housed here.\n",
    "team_pth"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\wb527163\\.conda\\envs\\geo\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3444: DtypeWarning: Columns (5) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  exec(code_obj, self.user_global_ns, self.user_ns)\n"
     ]
    },
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     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nodes = os.path.join(out_pth, \"drive_time_node.csv\")\n",
    "nodes = pd.read_csv(nodes)\n",
    "nodes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
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     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "inV_snap = os.path.join(out_pth, \"ag_snap.csv\") # V as in village or ville (point of origin)\n",
    "inV_snap = pd.read_csv(inV_snap)\n",
    "inV_snap.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prepare origins and road nodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\wb527163\\.conda\\envs\\geo\\lib\\site-packages\\pyproj\\crs\\crs.py:131: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n"
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       "      <td>12.067253</td>\n",
       "      <td>POINT (-12.29379 12.06725)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>670104023</td>\n",
       "      <td>3</td>\n",
       "      <td>-12.282907</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.411030</td>\n",
       "      <td>POINT (-12.28291 12.41103)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>670104201</td>\n",
       "      <td>3</td>\n",
       "      <td>-12.360983</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.512258</td>\n",
       "      <td>POINT (-12.36098 12.51226)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0    node_ID  street_count          x highway  ref          y  \\\n",
       "0           0  358284990             3 -12.323471     NaN  NaN  12.381189   \n",
       "1           1  358285037             3 -12.267195     NaN  NaN  12.534741   \n",
       "2           2  496429117             4 -12.293792     NaN  NaN  12.067253   \n",
       "3           3  670104023             3 -12.282907     NaN  NaN  12.411030   \n",
       "4           4  670104201             3 -12.360983     NaN  NaN  12.512258   \n",
       "\n",
       "                     geometry  \n",
       "0  POINT (-12.32347 12.38119)  \n",
       "1  POINT (-12.26720 12.53474)  \n",
       "2  POINT (-12.29379 12.06725)  \n",
       "3  POINT (-12.28291 12.41103)  \n",
       "4  POINT (-12.36098 12.51226)  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geometry = [Point(xy) for xy in zip(nodes.x, nodes.y)]\n",
    "crs = {'init': 'epsg:4326'} \n",
    "nodes = GeoDataFrame(nodes, crs=crs, geometry=geometry) \n",
    "nodes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed_ 0</th>\n",
       "      <th>mgrs_code</th>\n",
       "      <th>type</th>\n",
       "      <th>GlobalID</th>\n",
       "      <th>Shape_Leng</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>NN</th>\n",
       "      <th>NN_dist</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>28PCU1265_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{ED2CCDD5-C78F-40B6-A18A-3A01B61A4998}</td>\n",
       "      <td>0.004314</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>7761872879</td>\n",
       "      <td>396.520984</td>\n",
       "      <td>-16.721473</td>\n",
       "      <td>12.348636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>28PCU1365_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{372B104B-B208-4D14-84E2-8ABFD4D8C37A}</td>\n",
       "      <td>0.009910</td>\n",
       "      <td>0.000006</td>\n",
       "      <td>7761872860</td>\n",
       "      <td>918.665696</td>\n",
       "      <td>-16.716457</td>\n",
       "      <td>12.347887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>28PCU1365_02</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{D03C2B85-5F35-4EE8-8346-B83494628F26}</td>\n",
       "      <td>0.003754</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>7761872847</td>\n",
       "      <td>952.759215</td>\n",
       "      <td>-16.713855</td>\n",
       "      <td>12.350881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>28PCU1566_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{5EAFF1C3-6EE5-4F96-99FC-78F924454480}</td>\n",
       "      <td>0.004401</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>7761872847</td>\n",
       "      <td>1923.779554</td>\n",
       "      <td>-16.701275</td>\n",
       "      <td>12.355585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>28PCU1566_02</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{1D6A9E17-0D49-446D-A23B-7A47B155DC64}</td>\n",
       "      <td>0.005357</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>7761872847</td>\n",
       "      <td>2181.254121</td>\n",
       "      <td>-16.698774</td>\n",
       "      <td>12.356804</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  Unnamed_ 0     mgrs_code    type  \\\n",
       "0           0           0  28PCU1265_01  hamlet   \n",
       "1           1           1  28PCU1365_01  hamlet   \n",
       "2           2           2  28PCU1365_02  hamlet   \n",
       "3           3           3  28PCU1566_01  hamlet   \n",
       "4           4           4  28PCU1566_02  hamlet   \n",
       "\n",
       "                                 GlobalID  Shape_Leng  Shape_Area          NN  \\\n",
       "0  {ED2CCDD5-C78F-40B6-A18A-3A01B61A4998}    0.004314    0.000001  7761872879   \n",
       "1  {372B104B-B208-4D14-84E2-8ABFD4D8C37A}    0.009910    0.000006  7761872860   \n",
       "2  {D03C2B85-5F35-4EE8-8346-B83494628F26}    0.003754    0.000001  7761872847   \n",
       "3  {5EAFF1C3-6EE5-4F96-99FC-78F924454480}    0.004401    0.000002  7761872847   \n",
       "4  {1D6A9E17-0D49-446D-A23B-7A47B155DC64}    0.005357    0.000002  7761872847   \n",
       "\n",
       "       NN_dist          X          Y  \n",
       "0   396.520984 -16.721473  12.348636  \n",
       "1   918.665696 -16.716457  12.347887  \n",
       "2   952.759215 -16.713855  12.350881  \n",
       "3  1923.779554 -16.701275  12.355585  \n",
       "4  2181.254121 -16.698774  12.356804  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# I was having a lot of trouble creating a geodataframe from the snap csv in the settlements version. \n",
    "# Recreating the geometry field resolved it.\n",
    "inV_snap[\"geometry\"] = inV_snap[\"geometry\"].astype('str')\n",
    "inV_snap[\"geometry\"] = inV_snap[\"geometry\"].str.strip('POINT ')\n",
    "inV_snap[\"geometry\"] = inV_snap[\"geometry\"].str.strip('()')\n",
    "XY = inV_snap[\"geometry\"].str.split(\" \", expand=True)\n",
    "inV_snap[\"X\"] = XY[0]\n",
    "inV_snap[\"Y\"] = XY[1]\n",
    "inV_snap['X'] = inV_snap['X'].astype('float')\n",
    "inV_snap['Y'] = inV_snap['Y'].astype('float')\n",
    "inV_snap = inV_snap.drop(columns=['geometry'])\n",
    "inV_snap.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "geometry = [Point(xy) for xy in zip(inV_snap.x, inV_snap.y)]\n",
    "crs = 'epsg:4326' # If file is not saved as WGS84, make sure to change the CRS after this to match the road nodes.\n",
    "inV_snap = GeoDataFrame(inV_snap, crs=crs, geometry=geometry) \n",
    "inV_snap.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "inV_snap = inV_snap.to_crs(\"EPSG:4326\")\n",
    "nodes = nodes.to_crs(\"EPSG:4326\")\n",
    "inV_snap.crs == nodes.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n",
      "RangeIndex: 368843 entries, 0 to 368842\n",
      "Data columns (total 5 columns):\n",
      " #   Column      Non-Null Count   Dtype   \n",
      "---  ------      --------------   -----   \n",
      " 0   Unnamed: 0  368843 non-null  int64   \n",
      " 1   node_ID     368843 non-null  int64   \n",
      " 2   x           368843 non-null  float64 \n",
      " 3   y           368843 non-null  float64 \n",
      " 4   geometry    368843 non-null  geometry\n",
      "dtypes: float64(2), geometry(1), int64(2)\n",
      "memory usage: 14.1 MB\n"
     ]
    }
   ],
   "source": [
    "# Ensure nodes coordinates and unique ID field are in the right data type.\n",
    "# Most of the rows didn't merge correctly from the nodes layer the first time around because node's NN column was int32, not int64.\n",
    "nodes['x'] = nodes['x'].astype('float')\n",
    "nodes['y'] = nodes['y'].astype('float')\n",
    "nodes['node_ID'] = nodes['node_ID'].astype('int64')\n",
    "nodes = nodes.drop(columns=['street_count', 'highway', 'ref'])\n",
    "nodes.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vid</th>\n",
       "      <th>mgrs_code</th>\n",
       "      <th>type</th>\n",
       "      <th>GlobalID</th>\n",
       "      <th>Shape_Leng</th>\n",
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       "      <th>2</th>\n",
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       "      <td>28PCU1365_02</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>28PCU1566_01</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>28PCU1566_02</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{1D6A9E17-0D49-446D-A23B-7A47B155DC64}</td>\n",
       "      <td>0.005357</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>7761872847</td>\n",
       "      <td>2181.254121</td>\n",
       "      <td>-16.698774</td>\n",
       "      <td>12.356804</td>\n",
       "      <td>POINT (-16.69877 12.35680)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   vid     mgrs_code    type                                GlobalID  \\\n",
       "0    0  28PCU1265_01  hamlet  {ED2CCDD5-C78F-40B6-A18A-3A01B61A4998}   \n",
       "1    1  28PCU1365_01  hamlet  {372B104B-B208-4D14-84E2-8ABFD4D8C37A}   \n",
       "2    2  28PCU1365_02  hamlet  {D03C2B85-5F35-4EE8-8346-B83494628F26}   \n",
       "3    3  28PCU1566_01  hamlet  {5EAFF1C3-6EE5-4F96-99FC-78F924454480}   \n",
       "4    4  28PCU1566_02  hamlet  {1D6A9E17-0D49-446D-A23B-7A47B155DC64}   \n",
       "\n",
       "   Shape_Leng  Shape_Area          NN      NN_dist          X          Y  \\\n",
       "0    0.004314    0.000001  7761872879   396.520984 -16.721473  12.348636   \n",
       "1    0.009910    0.000006  7761872860   918.665696 -16.716457  12.347887   \n",
       "2    0.003754    0.000001  7761872847   952.759215 -16.713855  12.350881   \n",
       "3    0.004401    0.000002  7761872847  1923.779554 -16.701275  12.355585   \n",
       "4    0.005357    0.000002  7761872847  2181.254121 -16.698774  12.356804   \n",
       "\n",
       "                     geometry  \n",
       "0  POINT (-16.72147 12.34864)  \n",
       "1  POINT (-16.71646 12.34789)  \n",
       "2  POINT (-16.71386 12.35088)  \n",
       "3  POINT (-16.70128 12.35559)  \n",
       "4  POINT (-16.69877 12.35680)  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inV_snap = inV_snap.drop(columns=['Unnamed_ 0', 'Unnamed: 0.1', 'Unnamed: 0.1.1'])\n",
    "inV_snap.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n",
      "RangeIndex: 125886 entries, 0 to 125885\n",
      "Data columns (total 11 columns):\n",
      " #   Column      Non-Null Count   Dtype   \n",
      "---  ------      --------------   -----   \n",
      " 0   vid         125886 non-null  int64   \n",
      " 1   mgrs_code   125886 non-null  object  \n",
      " 2   type        125886 non-null  object  \n",
      " 3   GlobalID    125886 non-null  object  \n",
      " 4   Shape_Leng  125886 non-null  float64 \n",
      " 5   Shape_Area  125886 non-null  float64 \n",
      " 6   NN          125886 non-null  int64   \n",
      " 7   NN_dist     125886 non-null  float64 \n",
      " 8   X           125886 non-null  float64 \n",
      " 9   Y           125886 non-null  float64 \n",
      " 10  geometry    125886 non-null  geometry\n",
      "dtypes: float64(5), geometry(1), int64(2), object(3)\n",
      "memory usage: 10.6+ MB\n"
     ]
    }
   ],
   "source": [
    "inV_snap['ID_lc'] = inV_snap['ID_lc'].astype('int64')\n",
    "inV_snap.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prepare elevation raster"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Elevation: merge into a single tif"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
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       "      <td>-12.282907</td>\n",
       "      <td>12.411030</td>\n",
       "      <td>POINT (-12.28291 12.41103)</td>\n",
       "      <td>[204.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>670104201</td>\n",
       "      <td>-12.360983</td>\n",
       "      <td>12.512258</td>\n",
       "      <td>POINT (-12.36098 12.51226)</td>\n",
       "      <td>[175.0]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0    node_ID          x          y                    geometry  \\\n",
       "0           0  358284990 -12.323471  12.381189  POINT (-12.32347 12.38119)   \n",
       "1           1  358285037 -12.267195  12.534741  POINT (-12.26720 12.53474)   \n",
       "2           2  496429117 -12.293792  12.067253  POINT (-12.29379 12.06725)   \n",
       "3           3  670104023 -12.282907  12.411030  POINT (-12.28291 12.41103)   \n",
       "4           4  670104201 -12.360983  12.512258  POINT (-12.36098 12.51226)   \n",
       "\n",
       "       elev  \n",
       "0   [207.0]  \n",
       "1   [134.0]  \n",
       "2  [1429.0]  \n",
       "3   [204.0]  \n",
       "4   [175.0]  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read points from shapefile\n",
    "nodes.index = range(len(nodes))\n",
    "coords = [(x,y) for x, y in zip(nodes.x, nodes.y)]\n",
    "\n",
    "# Open the raster and store metadata\n",
    "src = rt.open('R:/SEN/GEO/Elevation/CWA_senegambia.tif')\n",
    "\n",
    "# Sample the raster at every point location and store values in DataFrame\n",
    "nodes['elev'] = [x for x in src.sample(coords)]\n",
    "\n",
    "nodes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
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       "      <th>3</th>\n",
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       "      <td>POINT (-12.28291 12.41103)</td>\n",
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       "   Unnamed: 0    node_ID          x          y                    geometry  \\\n",
       "0           0  358284990 -12.323471  12.381189  POINT (-12.32347 12.38119)   \n",
       "1           1  358285037 -12.267195  12.534741  POINT (-12.26720 12.53474)   \n",
       "2           2  496429117 -12.293792  12.067253  POINT (-12.29379 12.06725)   \n",
       "3           3  670104023 -12.282907  12.411030  POINT (-12.28291 12.41103)   \n",
       "4           4  670104201 -12.360983  12.512258  POINT (-12.36098 12.51226)   \n",
       "\n",
       "     elev  \n",
       "0   207.0  \n",
       "1   134.0  \n",
       "2  1429.0  \n",
       "3   204.0  \n",
       "4   175.0  "
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     },
     "execution_count": 20,
     "metadata": {},
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    }
   ],
   "source": [
    "# Remove the brackets from elevation variable.\n",
    "nodes['elev'] = nodes['elev'].astype(str)\n",
    "nodes['elev'] = nodes['elev'].str.strip('[]')\n",
    "nodes['elev'] = nodes['elev'].astype('float')\n",
    "nodes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
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       "<p>125886 rows × 12 columns</p>\n",
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      "text/plain": [
       "           vid     mgrs_code    type                                GlobalID  \\\n",
       "0            0  28PCU1265_01  hamlet  {ED2CCDD5-C78F-40B6-A18A-3A01B61A4998}   \n",
       "1            1  28PCU1365_01  hamlet  {372B104B-B208-4D14-84E2-8ABFD4D8C37A}   \n",
       "2            2  28PCU1365_02  hamlet  {D03C2B85-5F35-4EE8-8346-B83494628F26}   \n",
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       "...        ...           ...     ...                                     ...   \n",
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       "125882  125882  28QED6413_03  hamlet  {20205A44-8B9D-4FCE-B14C-53826594DB5A}   \n",
       "125883  125883  28QED6413_04  hamlet  {AC6A169C-FD0E-4DF6-BDAB-B69FBD04BFAF}   \n",
       "125884  125884  28QED6424_03  hamlet  {51593C65-B268-4BA1-8212-E43232C021FF}   \n",
       "125885  125885  28QED6438_03  hamlet  {05114E26-63E9-4384-9F9E-8533D8AE2F1F}   \n",
       "\n",
       "        Shape_Leng  Shape_Area          NN      NN_dist          X          Y  \\\n",
       "0         0.004314    0.000001  7761872879   396.520984 -16.721473  12.348636   \n",
       "1         0.009910    0.000006  7761872860   918.665696 -16.716457  12.347887   \n",
       "2         0.003754    0.000001  7761872847   952.759215 -16.713855  12.350881   \n",
       "3         0.004401    0.000002  7761872847  1923.779554 -16.701275  12.355585   \n",
       "4         0.005357    0.000002  7761872847  2181.254121 -16.698774  12.356804   \n",
       "...            ...         ...         ...          ...        ...        ...   \n",
       "125881    0.005397    0.000002  8592243241  5089.086102 -14.397828  16.394143   \n",
       "125882    0.003610    0.000001  8592243457  4062.119008 -14.397473  16.405677   \n",
       "125883    0.015471    0.000008  8592243457  4008.851333 -14.400364  16.404303   \n",
       "125884    0.003883    0.000001  3646207611  1826.174300 -14.396244  16.497151   \n",
       "125885    0.007869    0.000004  8538238600   840.588582 -14.395109  16.631548   \n",
       "\n",
       "                          geometry    elev  \n",
       "0       POINT (-16.72147 12.34864)  [13.0]  \n",
       "1       POINT (-16.71646 12.34789)  [12.0]  \n",
       "2       POINT (-16.71386 12.35088)   [7.0]  \n",
       "3       POINT (-16.70128 12.35559)   [7.0]  \n",
       "4       POINT (-16.69877 12.35680)   [5.0]  \n",
       "...                            ...     ...  \n",
       "125881  POINT (-14.39783 16.39414)  [24.0]  \n",
       "125882  POINT (-14.39747 16.40568)  [23.0]  \n",
       "125883  POINT (-14.40036 16.40430)  [24.0]  \n",
       "125884  POINT (-14.39624 16.49715)   [7.0]  \n",
       "125885  POINT (-14.39511 16.63155)  [14.0]  \n",
       "\n",
       "[125886 rows x 12 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read points from shapefile\n",
    "inV_snap.index = range(len(inV_snap))\n",
    "coords = [(x,y) for x, y in zip(inV_snap.X, inV_snap.Y)]\n",
    "\n",
    "# Sample the raster at every point location and store values in DataFrame\n",
    "inV_snap['elev'] = [x for x in src.sample(coords)]\n",
    "inV_snap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
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       "      <td>POINT (-16.72147 12.34864)</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>28PCU1365_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{372B104B-B208-4D14-84E2-8ABFD4D8C37A}</td>\n",
       "      <td>0.009910</td>\n",
       "      <td>0.000006</td>\n",
       "      <td>7761872860</td>\n",
       "      <td>918.665696</td>\n",
       "      <td>-16.716457</td>\n",
       "      <td>12.347887</td>\n",
       "      <td>POINT (-16.71646 12.34789)</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>28PCU1365_02</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{D03C2B85-5F35-4EE8-8346-B83494628F26}</td>\n",
       "      <td>0.003754</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>7761872847</td>\n",
       "      <td>952.759215</td>\n",
       "      <td>-16.713855</td>\n",
       "      <td>12.350881</td>\n",
       "      <td>POINT (-16.71386 12.35088)</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>28PCU1566_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{5EAFF1C3-6EE5-4F96-99FC-78F924454480}</td>\n",
       "      <td>0.004401</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>7761872847</td>\n",
       "      <td>1923.779554</td>\n",
       "      <td>-16.701275</td>\n",
       "      <td>12.355585</td>\n",
       "      <td>POINT (-16.70128 12.35559)</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>28PCU1566_02</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{1D6A9E17-0D49-446D-A23B-7A47B155DC64}</td>\n",
       "      <td>0.005357</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>7761872847</td>\n",
       "      <td>2181.254121</td>\n",
       "      <td>-16.698774</td>\n",
       "      <td>12.356804</td>\n",
       "      <td>POINT (-16.69877 12.35680)</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   vid     mgrs_code    type                                GlobalID  \\\n",
       "0    0  28PCU1265_01  hamlet  {ED2CCDD5-C78F-40B6-A18A-3A01B61A4998}   \n",
       "1    1  28PCU1365_01  hamlet  {372B104B-B208-4D14-84E2-8ABFD4D8C37A}   \n",
       "2    2  28PCU1365_02  hamlet  {D03C2B85-5F35-4EE8-8346-B83494628F26}   \n",
       "3    3  28PCU1566_01  hamlet  {5EAFF1C3-6EE5-4F96-99FC-78F924454480}   \n",
       "4    4  28PCU1566_02  hamlet  {1D6A9E17-0D49-446D-A23B-7A47B155DC64}   \n",
       "\n",
       "   Shape_Leng  Shape_Area          NN      NN_dist          X          Y  \\\n",
       "0    0.004314    0.000001  7761872879   396.520984 -16.721473  12.348636   \n",
       "1    0.009910    0.000006  7761872860   918.665696 -16.716457  12.347887   \n",
       "2    0.003754    0.000001  7761872847   952.759215 -16.713855  12.350881   \n",
       "3    0.004401    0.000002  7761872847  1923.779554 -16.701275  12.355585   \n",
       "4    0.005357    0.000002  7761872847  2181.254121 -16.698774  12.356804   \n",
       "\n",
       "                     geometry  elev  \n",
       "0  POINT (-16.72147 12.34864)  13.0  \n",
       "1  POINT (-16.71646 12.34789)  12.0  \n",
       "2  POINT (-16.71386 12.35088)   7.0  \n",
       "3  POINT (-16.70128 12.35559)   7.0  \n",
       "4  POINT (-16.69877 12.35680)   5.0  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inV_snap['elev'] = inV_snap['elev'].astype(str)\n",
    "inV_snap['elev'] = inV_snap['elev'].str.strip('[]')\n",
    "inV_snap['elev'] = inV_snap['elev'].astype('float')\n",
    "inV_snap.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Elevation adjusted walk time to road."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%% If starting new session, reload graph from file\n",
    "gTime = nx.read_gpickle(\"SEN-Cdrive/outputs/gTime.pickle\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Next, do the same for origin points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n",
      "RangeIndex: 368843 entries, 0 to 368842\n",
      "Data columns (total 6 columns):\n",
      " #   Column      Non-Null Count   Dtype   \n",
      "---  ------      --------------   -----   \n",
      " 0   Unnamed: 0  368843 non-null  int64   \n",
      " 1   NN          368843 non-null  int64   \n",
      " 2   x           368843 non-null  float64 \n",
      " 3   y           368843 non-null  float64 \n",
      " 4   geometry    368843 non-null  geometry\n",
      " 5   elev        368843 non-null  float64 \n",
      "dtypes: float64(3), geometry(1), int64(2)\n",
      "memory usage: 16.9 MB\n"
     ]
    }
   ],
   "source": [
    "nodes.rename(columns={'node_ID':'NN'}, inplace=True)\n",
    "nodes.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vid</th>\n",
       "      <th>mgrs_code</th>\n",
       "      <th>type</th>\n",
       "      <th>GlobalID</th>\n",
       "      <th>Shape_Leng</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>NN</th>\n",
       "      <th>NN_dist</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>geometry_x</th>\n",
       "      <th>elev_x</th>\n",
       "      <th>Unnamed: 0</th>\n",
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       "      <th>geometry_y</th>\n",
       "      <th>elev_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>28PCU1265_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{ED2CCDD5-C78F-40B6-A18A-3A01B61A4998}</td>\n",
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       "      <td>POINT (-16.72456 12.35055)</td>\n",
       "      <td>6.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>28PCU1365_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{372B104B-B208-4D14-84E2-8ABFD4D8C37A}</td>\n",
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       "      <td>0.000006</td>\n",
       "      <td>7761872860</td>\n",
       "      <td>918.665696</td>\n",
       "      <td>-16.716457</td>\n",
       "      <td>12.347887</td>\n",
       "      <td>POINT (-16.71646 12.34789)</td>\n",
       "      <td>12.0</td>\n",
       "      <td>202441</td>\n",
       "      <td>-16.722870</td>\n",
       "      <td>12.353291</td>\n",
       "      <td>POINT (-16.72287 12.35329)</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>28PCU1365_02</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{D03C2B85-5F35-4EE8-8346-B83494628F26}</td>\n",
       "      <td>0.003754</td>\n",
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       "      <td>952.759215</td>\n",
       "      <td>-16.713855</td>\n",
       "      <td>12.350881</td>\n",
       "      <td>POINT (-16.71386 12.35088)</td>\n",
       "      <td>7.0</td>\n",
       "      <td>202440</td>\n",
       "      <td>-16.718793</td>\n",
       "      <td>12.357995</td>\n",
       "      <td>POINT (-16.71879 12.35799)</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>28PCU1566_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{5EAFF1C3-6EE5-4F96-99FC-78F924454480}</td>\n",
       "      <td>0.004401</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>7761872847</td>\n",
       "      <td>1923.779554</td>\n",
       "      <td>-16.701275</td>\n",
       "      <td>12.355585</td>\n",
       "      <td>POINT (-16.70128 12.35559)</td>\n",
       "      <td>7.0</td>\n",
       "      <td>202440</td>\n",
       "      <td>-16.718793</td>\n",
       "      <td>12.357995</td>\n",
       "      <td>POINT (-16.71879 12.35799)</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>28PCU1566_02</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{1D6A9E17-0D49-446D-A23B-7A47B155DC64}</td>\n",
       "      <td>0.005357</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>7761872847</td>\n",
       "      <td>2181.254121</td>\n",
       "      <td>-16.698774</td>\n",
       "      <td>12.356804</td>\n",
       "      <td>POINT (-16.69877 12.35680)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>202440</td>\n",
       "      <td>-16.718793</td>\n",
       "      <td>12.357995</td>\n",
       "      <td>POINT (-16.71879 12.35799)</td>\n",
       "      <td>14.0</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>125881</th>\n",
       "      <td>125881</td>\n",
       "      <td>28QED6412_03</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{5555A010-36B2-47D2-96C4-BDD1E59111ED}</td>\n",
       "      <td>0.005397</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>8592243241</td>\n",
       "      <td>5089.086102</td>\n",
       "      <td>-14.397828</td>\n",
       "      <td>16.394143</td>\n",
       "      <td>POINT (-14.39783 16.39414)</td>\n",
       "      <td>24.0</td>\n",
       "      <td>47115</td>\n",
       "      <td>-14.424516</td>\n",
       "      <td>16.432258</td>\n",
       "      <td>POINT (-14.42452 16.43226)</td>\n",
       "      <td>22.0</td>\n",
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       "    <tr>\n",
       "      <th>125882</th>\n",
       "      <td>125882</td>\n",
       "      <td>28QED6413_03</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{20205A44-8B9D-4FCE-B14C-53826594DB5A}</td>\n",
       "      <td>0.003610</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>8592243457</td>\n",
       "      <td>4062.119008</td>\n",
       "      <td>-14.397473</td>\n",
       "      <td>16.405677</td>\n",
       "      <td>POINT (-14.39747 16.40568)</td>\n",
       "      <td>23.0</td>\n",
       "      <td>47199</td>\n",
       "      <td>-14.420648</td>\n",
       "      <td>16.434798</td>\n",
       "      <td>POINT (-14.42065 16.43480)</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125883</th>\n",
       "      <td>125883</td>\n",
       "      <td>28QED6413_04</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{AC6A169C-FD0E-4DF6-BDAB-B69FBD04BFAF}</td>\n",
       "      <td>0.015471</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>8592243457</td>\n",
       "      <td>4008.851333</td>\n",
       "      <td>-14.400364</td>\n",
       "      <td>16.404303</td>\n",
       "      <td>POINT (-14.40036 16.40430)</td>\n",
       "      <td>24.0</td>\n",
       "      <td>47199</td>\n",
       "      <td>-14.420648</td>\n",
       "      <td>16.434798</td>\n",
       "      <td>POINT (-14.42065 16.43480)</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125884</th>\n",
       "      <td>125884</td>\n",
       "      <td>28QED6424_03</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{51593C65-B268-4BA1-8212-E43232C021FF}</td>\n",
       "      <td>0.003883</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>3646207611</td>\n",
       "      <td>1826.174300</td>\n",
       "      <td>-14.396244</td>\n",
       "      <td>16.497151</td>\n",
       "      <td>POINT (-14.39624 16.49715)</td>\n",
       "      <td>7.0</td>\n",
       "      <td>46827</td>\n",
       "      <td>-14.412651</td>\n",
       "      <td>16.492467</td>\n",
       "      <td>POINT (-14.41265 16.49247)</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125885</th>\n",
       "      <td>125885</td>\n",
       "      <td>28QED6438_03</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{05114E26-63E9-4384-9F9E-8533D8AE2F1F}</td>\n",
       "      <td>0.007869</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>8538238600</td>\n",
       "      <td>840.588582</td>\n",
       "      <td>-14.395109</td>\n",
       "      <td>16.631548</td>\n",
       "      <td>POINT (-14.39511 16.63155)</td>\n",
       "      <td>14.0</td>\n",
       "      <td>47767</td>\n",
       "      <td>-14.402797</td>\n",
       "      <td>16.629875</td>\n",
       "      <td>POINT (-14.40280 16.62987)</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>125886 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           vid     mgrs_code    type                                GlobalID  \\\n",
       "0            0  28PCU1265_01  hamlet  {ED2CCDD5-C78F-40B6-A18A-3A01B61A4998}   \n",
       "1            1  28PCU1365_01  hamlet  {372B104B-B208-4D14-84E2-8ABFD4D8C37A}   \n",
       "2            2  28PCU1365_02  hamlet  {D03C2B85-5F35-4EE8-8346-B83494628F26}   \n",
       "3            3  28PCU1566_01  hamlet  {5EAFF1C3-6EE5-4F96-99FC-78F924454480}   \n",
       "4            4  28PCU1566_02  hamlet  {1D6A9E17-0D49-446D-A23B-7A47B155DC64}   \n",
       "...        ...           ...     ...                                     ...   \n",
       "125881  125881  28QED6412_03  hamlet  {5555A010-36B2-47D2-96C4-BDD1E59111ED}   \n",
       "125882  125882  28QED6413_03  hamlet  {20205A44-8B9D-4FCE-B14C-53826594DB5A}   \n",
       "125883  125883  28QED6413_04  hamlet  {AC6A169C-FD0E-4DF6-BDAB-B69FBD04BFAF}   \n",
       "125884  125884  28QED6424_03  hamlet  {51593C65-B268-4BA1-8212-E43232C021FF}   \n",
       "125885  125885  28QED6438_03  hamlet  {05114E26-63E9-4384-9F9E-8533D8AE2F1F}   \n",
       "\n",
       "        Shape_Leng  Shape_Area          NN      NN_dist          X          Y  \\\n",
       "0         0.004314    0.000001  7761872879   396.520984 -16.721473  12.348636   \n",
       "1         0.009910    0.000006  7761872860   918.665696 -16.716457  12.347887   \n",
       "2         0.003754    0.000001  7761872847   952.759215 -16.713855  12.350881   \n",
       "3         0.004401    0.000002  7761872847  1923.779554 -16.701275  12.355585   \n",
       "4         0.005357    0.000002  7761872847  2181.254121 -16.698774  12.356804   \n",
       "...            ...         ...         ...          ...        ...        ...   \n",
       "125881    0.005397    0.000002  8592243241  5089.086102 -14.397828  16.394143   \n",
       "125882    0.003610    0.000001  8592243457  4062.119008 -14.397473  16.405677   \n",
       "125883    0.015471    0.000008  8592243457  4008.851333 -14.400364  16.404303   \n",
       "125884    0.003883    0.000001  3646207611  1826.174300 -14.396244  16.497151   \n",
       "125885    0.007869    0.000004  8538238600   840.588582 -14.395109  16.631548   \n",
       "\n",
       "                        geometry_x  elev_x  Unnamed: 0          x          y  \\\n",
       "0       POINT (-16.72147 12.34864)    13.0      202442 -16.724557  12.350548   \n",
       "1       POINT (-16.71646 12.34789)    12.0      202441 -16.722870  12.353291   \n",
       "2       POINT (-16.71386 12.35088)     7.0      202440 -16.718793  12.357995   \n",
       "3       POINT (-16.70128 12.35559)     7.0      202440 -16.718793  12.357995   \n",
       "4       POINT (-16.69877 12.35680)     5.0      202440 -16.718793  12.357995   \n",
       "...                            ...     ...         ...        ...        ...   \n",
       "125881  POINT (-14.39783 16.39414)    24.0       47115 -14.424516  16.432258   \n",
       "125882  POINT (-14.39747 16.40568)    23.0       47199 -14.420648  16.434798   \n",
       "125883  POINT (-14.40036 16.40430)    24.0       47199 -14.420648  16.434798   \n",
       "125884  POINT (-14.39624 16.49715)     7.0       46827 -14.412651  16.492467   \n",
       "125885  POINT (-14.39511 16.63155)    14.0       47767 -14.402797  16.629875   \n",
       "\n",
       "                        geometry_y  elev_y  \n",
       "0       POINT (-16.72456 12.35055)     6.0  \n",
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       "3       POINT (-16.71879 12.35799)    14.0  \n",
       "4       POINT (-16.71879 12.35799)    14.0  \n",
       "...                            ...     ...  \n",
       "125881  POINT (-14.42452 16.43226)    22.0  \n",
       "125882  POINT (-14.42065 16.43480)    18.0  \n",
       "125883  POINT (-14.42065 16.43480)    18.0  \n",
       "125884  POINT (-14.41265 16.49247)    12.0  \n",
       "125885  POINT (-14.40280 16.62987)    17.0  \n",
       "\n",
       "[125886 rows x 17 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zvalues = pd.merge(inV_snap, nodes, on='NN', how='left')\n",
    "zvalues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "vid              int64\n",
       "mgrs_code       object\n",
       "type            object\n",
       "GlobalID        object\n",
       "Shape_Leng     float64\n",
       "Shape_Area     float64\n",
       "NN               int64\n",
       "NN_dist        float64\n",
       "X              float64\n",
       "Y              float64\n",
       "geometry_x    geometry\n",
       "v_elev         float64\n",
       "Unnamed: 0       int64\n",
       "x              float64\n",
       "y              float64\n",
       "geometry_y    geometry\n",
       "node_elev      float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zvalues.rename(columns={'elev_y':'node_elev'}, inplace=True)\n",
    "zvalues.rename(columns={'elev_x':'v_elev'}, inplace=True)\n",
    "zvalues.dtypes # Make sure these two columns are float."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Time is in seconds.\n",
    "def generate_walktimes(df, start = 'v_elev', end = 'node_elev', dist = 'NN_dist', max_walkspeed = 6, min_speed = 0.1):\n",
    "    # Irmischer & Clarke hiking function\n",
    "    def speed(incline_ratio, max_speed):\n",
    "        walkspeed = (0.95 * (0.11 + np.exp(-(np.square(incline_ratio + 0.05) / np.square(2*30))))) * 3.6\n",
    "        return walkspeed\n",
    "\n",
    "    speeds = {}\n",
    "    times = {}\n",
    "\n",
    "    for index, data in df.iterrows():\n",
    "        if data[dist] > 0:\n",
    "            delta_elevation = data[end] - data[start]\n",
    "            incline_ratio = delta_elevation / data[dist]\n",
    "            speed_kmph = speed(incline_ratio = incline_ratio, max_speed = max_walkspeed)\n",
    "            speed_kmph = max(speed_kmph, min_speed)\n",
    "            speeds[index] = (speed_kmph)\n",
    "            times[index] = (data[dist] / 1000 * 3600 / speed_kmph)\n",
    "\n",
    "    speed_df = pd.DataFrame.from_dict(speeds, orient = 'index')\n",
    "    time_df = pd.DataFrame.from_dict(times, orient = 'index')\n",
    "\n",
    "    df['walkspeed'] = speed_df[0]\n",
    "    df['walk_time'] = time_df[0]\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vid</th>\n",
       "      <th>mgrs_code</th>\n",
       "      <th>type</th>\n",
       "      <th>GlobalID</th>\n",
       "      <th>Shape_Leng</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>NN</th>\n",
       "      <th>NN_dist</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>geometry_x</th>\n",
       "      <th>v_elev</th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>geometry_y</th>\n",
       "      <th>node_elev</th>\n",
       "      <th>walkspeed</th>\n",
       "      <th>walk_time</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>28PCU1365_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{372B104B-B208-4D14-84E2-8ABFD4D8C37A}</td>\n",
       "      <td>0.009910</td>\n",
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       "      <td>28PCU1365_02</td>\n",
       "      <td>hamlet</td>\n",
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       "      <td>0.003754</td>\n",
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       "      <td>-16.713855</td>\n",
       "      <td>12.350881</td>\n",
       "      <td>POINT (-16.71386 12.35088)</td>\n",
       "      <td>7.0</td>\n",
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       "      <td>-16.718793</td>\n",
       "      <td>12.357995</td>\n",
       "      <td>POINT (-16.71879 12.35799)</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3.796197</td>\n",
       "      <td>903.518254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>28PCU1566_01</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{5EAFF1C3-6EE5-4F96-99FC-78F924454480}</td>\n",
       "      <td>0.004401</td>\n",
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       "      <td>14.0</td>\n",
       "      <td>3.796197</td>\n",
       "      <td>1824.353665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>28PCU1566_02</td>\n",
       "      <td>hamlet</td>\n",
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       "      <td>0.005357</td>\n",
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       "      <th>125881</th>\n",
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       "      <td>POINT (-14.42452 16.43226)</td>\n",
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       "      <td>3.796198</td>\n",
       "      <td>4826.068502</td>\n",
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       "    <tr>\n",
       "      <th>125882</th>\n",
       "      <td>125882</td>\n",
       "      <td>28QED6413_03</td>\n",
       "      <td>hamlet</td>\n",
       "      <td>{20205A44-8B9D-4FCE-B14C-53826594DB5A}</td>\n",
       "      <td>0.003610</td>\n",
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       "      <td>8592243457</td>\n",
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       "    <tr>\n",
       "      <th>125883</th>\n",
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       "      <td>{AC6A169C-FD0E-4DF6-BDAB-B69FBD04BFAF}</td>\n",
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       "    <tr>\n",
       "      <th>125884</th>\n",
       "      <td>125884</td>\n",
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       "    <tr>\n",
       "      <th>125885</th>\n",
       "      <td>125885</td>\n",
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       "<p>125886 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           vid     mgrs_code    type                                GlobalID  \\\n",
       "0            0  28PCU1265_01  hamlet  {ED2CCDD5-C78F-40B6-A18A-3A01B61A4998}   \n",
       "1            1  28PCU1365_01  hamlet  {372B104B-B208-4D14-84E2-8ABFD4D8C37A}   \n",
       "2            2  28PCU1365_02  hamlet  {D03C2B85-5F35-4EE8-8346-B83494628F26}   \n",
       "3            3  28PCU1566_01  hamlet  {5EAFF1C3-6EE5-4F96-99FC-78F924454480}   \n",
       "4            4  28PCU1566_02  hamlet  {1D6A9E17-0D49-446D-A23B-7A47B155DC64}   \n",
       "...        ...           ...     ...                                     ...   \n",
       "125881  125881  28QED6412_03  hamlet  {5555A010-36B2-47D2-96C4-BDD1E59111ED}   \n",
       "125882  125882  28QED6413_03  hamlet  {20205A44-8B9D-4FCE-B14C-53826594DB5A}   \n",
       "125883  125883  28QED6413_04  hamlet  {AC6A169C-FD0E-4DF6-BDAB-B69FBD04BFAF}   \n",
       "125884  125884  28QED6424_03  hamlet  {51593C65-B268-4BA1-8212-E43232C021FF}   \n",
       "125885  125885  28QED6438_03  hamlet  {05114E26-63E9-4384-9F9E-8533D8AE2F1F}   \n",
       "\n",
       "        Shape_Leng  Shape_Area          NN      NN_dist          X          Y  \\\n",
       "0         0.004314    0.000001  7761872879   396.520984 -16.721473  12.348636   \n",
       "1         0.009910    0.000006  7761872860   918.665696 -16.716457  12.347887   \n",
       "2         0.003754    0.000001  7761872847   952.759215 -16.713855  12.350881   \n",
       "3         0.004401    0.000002  7761872847  1923.779554 -16.701275  12.355585   \n",
       "4         0.005357    0.000002  7761872847  2181.254121 -16.698774  12.356804   \n",
       "...            ...         ...         ...          ...        ...        ...   \n",
       "125881    0.005397    0.000002  8592243241  5089.086102 -14.397828  16.394143   \n",
       "125882    0.003610    0.000001  8592243457  4062.119008 -14.397473  16.405677   \n",
       "125883    0.015471    0.000008  8592243457  4008.851333 -14.400364  16.404303   \n",
       "125884    0.003883    0.000001  3646207611  1826.174300 -14.396244  16.497151   \n",
       "125885    0.007869    0.000004  8538238600   840.588582 -14.395109  16.631548   \n",
       "\n",
       "                        geometry_x  v_elev  Unnamed: 0          x          y  \\\n",
       "0       POINT (-16.72147 12.34864)    13.0      202442 -16.724557  12.350548   \n",
       "1       POINT (-16.71646 12.34789)    12.0      202441 -16.722870  12.353291   \n",
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       "4       POINT (-16.69877 12.35680)     5.0      202440 -16.718793  12.357995   \n",
       "...                            ...     ...         ...        ...        ...   \n",
       "125881  POINT (-14.39783 16.39414)    24.0       47115 -14.424516  16.432258   \n",
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       "125883  POINT (-14.40036 16.40430)    24.0       47199 -14.420648  16.434798   \n",
       "125884  POINT (-14.39624 16.49715)     7.0       46827 -14.412651  16.492467   \n",
       "125885  POINT (-14.39511 16.63155)    14.0       47767 -14.402797  16.629875   \n",
       "\n",
       "                        geometry_y  node_elev  walkspeed    walk_time  \n",
       "0       POINT (-16.72456 12.35055)        6.0   3.796199   376.027584  \n",
       "1       POINT (-16.72287 12.35329)       18.0   3.796197   871.186753  \n",
       "2       POINT (-16.71879 12.35799)       14.0   3.796197   903.518254  \n",
       "3       POINT (-16.71879 12.35799)       14.0   3.796197  1824.353665  \n",
       "4       POINT (-16.71879 12.35799)       14.0   3.796197  2068.521309  \n",
       "...                            ...        ...        ...          ...  \n",
       "125881  POINT (-14.42452 16.43226)       22.0   3.796198  4826.068502  \n",
       "125882  POINT (-14.42065 16.43480)       18.0   3.796198  3852.177739  \n",
       "125883  POINT (-14.42065 16.43480)       18.0   3.796198  3801.663057  \n",
       "125884  POINT (-14.41265 16.49247)       12.0   3.796197  1731.792860  \n",
       "125885  POINT (-14.40280 16.62987)       17.0   3.796197   797.144795  \n",
       "\n",
       "[125886 rows x 19 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zwalk = generate_walktimes(zvalues) # Took a couple seconds.\n",
    "zwalk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "vid           0\n",
       "mgrs_code     0\n",
       "type          0\n",
       "GlobalID      0\n",
       "Shape_Leng    0\n",
       "Shape_Area    0\n",
       "NN            0\n",
       "NN_dist       0\n",
       "X             0\n",
       "Y             0\n",
       "geometry_x    0\n",
       "v_elev        0\n",
       "Unnamed: 0    0\n",
       "x             0\n",
       "y             0\n",
       "geometry_y    0\n",
       "node_elev     0\n",
       "walkspeed     0\n",
       "walk_time     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zwalk.isna().sum() # Make sure the rows merged correctly. If they didn't, double check the dtypes on NN to make sure they were the same in the nodes and snap dataframes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n",
      "Int64Index: 125886 entries, 0 to 125885\n",
      "Data columns (total 19 columns):\n",
      " #   Column      Non-Null Count   Dtype   \n",
      "---  ------      --------------   -----   \n",
      " 0   vid         125886 non-null  int64   \n",
      " 1   mgrs_code   125886 non-null  object  \n",
      " 2   type        125886 non-null  object  \n",
      " 3   GlobalID    125886 non-null  object  \n",
      " 4   Shape_Leng  125886 non-null  float64 \n",
      " 5   Shape_Area  125886 non-null  float64 \n",
      " 6   NN          125886 non-null  int64   \n",
      " 7   NN_dist     125886 non-null  float64 \n",
      " 8   X           125886 non-null  float64 \n",
      " 9   Y           125886 non-null  float64 \n",
      " 10  geometry_x  125886 non-null  geometry\n",
      " 11  v_elev      125886 non-null  float64 \n",
      " 12  Unnamed: 0  125886 non-null  int64   \n",
      " 13  x           125886 non-null  float64 \n",
      " 14  y           125886 non-null  float64 \n",
      " 15  geometry_y  125886 non-null  geometry\n",
      " 16  node_elev   125886 non-null  float64 \n",
      " 17  walkspeed   125886 non-null  float64 \n",
      " 18  walk_time   125886 non-null  float64 \n",
      "dtypes: float64(11), geometry(2), int64(3), object(3)\n",
      "memory usage: 19.2+ MB\n"
     ]
    }
   ],
   "source": [
    "zwalk.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "zwalk.to_csv('SEN-Cdrive/outputs/fromagriculture/zwalk_intermediatefile.csv', index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "vid             int64\n",
       "GlobalID       object\n",
       "NN              int64\n",
       "NN_dist       float64\n",
       "X_haml        float64\n",
       "Y_haml        float64\n",
       "geom_haml    geometry\n",
       "v_elev        float64\n",
       "X_road        float64\n",
       "Y_road        float64\n",
       "geom_road    geometry\n",
       "node_elev     float64\n",
       "walkspeed     float64\n",
       "walk_time     float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Clean up the file for only the necessary columns.\n",
    "zwalk2 = zwalk.drop(columns=['mgrs_code','type', 'Shape_Leng', 'Shape_Area', 'Unnamed: 0'])\n",
    "zwalk2.rename(columns={'X':'X_haml'}, inplace=True)\n",
    "zwalk2.rename(columns={'Y':'Y_haml'}, inplace=True)\n",
    "zwalk2.rename(columns={'geometry_x':'geom_haml'}, inplace=True)\n",
    "zwalk2.rename(columns={'x':'X_road'}, inplace=True)\n",
    "zwalk2.rename(columns={'y':'Y_road'}, inplace=True)\n",
    "zwalk2.rename(columns={'geometry_y':'geom_road'}, inplace=True)\n",
    "zwalk2.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "           vid                                GlobalID          NN  \\\n",
       "0            0  {ED2CCDD5-C78F-40B6-A18A-3A01B61A4998}  7761872879   \n",
       "1            1  {372B104B-B208-4D14-84E2-8ABFD4D8C37A}  7761872860   \n",
       "2            2  {D03C2B85-5F35-4EE8-8346-B83494628F26}  7761872847   \n",
       "3            3  {5EAFF1C3-6EE5-4F96-99FC-78F924454480}  7761872847   \n",
       "4            4  {1D6A9E17-0D49-446D-A23B-7A47B155DC64}  7761872847   \n",
       "...        ...                                     ...         ...   \n",
       "125881  125881  {5555A010-36B2-47D2-96C4-BDD1E59111ED}  8592243241   \n",
       "125882  125882  {20205A44-8B9D-4FCE-B14C-53826594DB5A}  8592243457   \n",
       "125883  125883  {AC6A169C-FD0E-4DF6-BDAB-B69FBD04BFAF}  8592243457   \n",
       "125884  125884  {51593C65-B268-4BA1-8212-E43232C021FF}  3646207611   \n",
       "125885  125885  {05114E26-63E9-4384-9F9E-8533D8AE2F1F}  8538238600   \n",
       "\n",
       "            NN_dist     X_haml     Y_haml                   geom_haml  v_elev  \\\n",
       "0        396.520984 -16.721473  12.348636  POINT (-16.72147 12.34864)    13.0   \n",
       "1        918.665696 -16.716457  12.347887  POINT (-16.71646 12.34789)    12.0   \n",
       "2        952.759215 -16.713855  12.350881  POINT (-16.71386 12.35088)     7.0   \n",
       "3       1923.779554 -16.701275  12.355585  POINT (-16.70128 12.35559)     7.0   \n",
       "4       2181.254121 -16.698774  12.356804  POINT (-16.69877 12.35680)     5.0   \n",
       "...             ...        ...        ...                         ...     ...   \n",
       "125881  5089.086102 -14.397828  16.394143  POINT (-14.39783 16.39414)    24.0   \n",
       "125882  4062.119008 -14.397473  16.405677  POINT (-14.39747 16.40568)    23.0   \n",
       "125883  4008.851333 -14.400364  16.404303  POINT (-14.40036 16.40430)    24.0   \n",
       "125884  1826.174300 -14.396244  16.497151  POINT (-14.39624 16.49715)     7.0   \n",
       "125885   840.588582 -14.395109  16.631548  POINT (-14.39511 16.63155)    14.0   \n",
       "\n",
       "           X_road     Y_road                   geom_road  node_elev  \\\n",
       "0      -16.724557  12.350548  POINT (-16.72456 12.35055)        6.0   \n",
       "1      -16.722870  12.353291  POINT (-16.72287 12.35329)       18.0   \n",
       "2      -16.718793  12.357995  POINT (-16.71879 12.35799)       14.0   \n",
       "3      -16.718793  12.357995  POINT (-16.71879 12.35799)       14.0   \n",
       "4      -16.718793  12.357995  POINT (-16.71879 12.35799)       14.0   \n",
       "...           ...        ...                         ...        ...   \n",
       "125881 -14.424516  16.432258  POINT (-14.42452 16.43226)       22.0   \n",
       "125882 -14.420648  16.434798  POINT (-14.42065 16.43480)       18.0   \n",
       "125883 -14.420648  16.434798  POINT (-14.42065 16.43480)       18.0   \n",
       "125884 -14.412651  16.492467  POINT (-14.41265 16.49247)       12.0   \n",
       "125885 -14.402797  16.629875  POINT (-14.40280 16.62987)       17.0   \n",
       "\n",
       "        walkspeed  walk_time  \n",
       "0        3.796199   6.267126  \n",
       "1        3.796197  14.519779  \n",
       "2        3.796197  15.058638  \n",
       "3        3.796197  30.405894  \n",
       "4        3.796197  34.475355  \n",
       "...           ...        ...  \n",
       "125881   3.796198  80.434475  \n",
       "125882   3.796198  64.202962  \n",
       "125883   3.796198  63.361051  \n",
       "125884   3.796197  28.863214  \n",
       "125885   3.796197  13.285747  \n",
       "\n",
       "[125886 rows x 14 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert from seconds to minutes\n",
    "zwalk2['walk_time'] = zwalk2['walk_time'] / 60\n",
    "zwalk2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save to disk.\n",
    "zwalk2.to_csv('SEN-Cdrive/outputs/fromagriculture/zwalk.csv', index=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create multi-modal travel times by combining walk time to road with drive time to nth nearest service."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>vid</th>\n",
       "      <th>GlobalID</th>\n",
       "      <th>NN</th>\n",
       "      <th>NN_dist</th>\n",
       "      <th>X_haml</th>\n",
       "      <th>Y_haml</th>\n",
       "      <th>geom_haml</th>\n",
       "      <th>v_elev</th>\n",
       "      <th>X_road</th>\n",
       "      <th>Y_road</th>\n",
       "      <th>geom_road</th>\n",
       "      <th>node_elev</th>\n",
       "      <th>walkspeed</th>\n",
       "      <th>walk_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>{ED2CCDD5-C78F-40B6-A18A-3A01B61A4998}</td>\n",
       "      <td>7761872879</td>\n",
       "      <td>396.520984</td>\n",
       "      <td>-16.721473</td>\n",
       "      <td>12.348636</td>\n",
       "      <td>POINT (-16.721473282454415 12.348636090165247)</td>\n",
       "      <td>13.0</td>\n",
       "      <td>-16.724557</td>\n",
       "      <td>12.350548</td>\n",
       "      <td>POINT (-16.7245571 12.3505478)</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.796199</td>\n",
       "      <td>6.267126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>{372B104B-B208-4D14-84E2-8ABFD4D8C37A}</td>\n",
       "      <td>7761872860</td>\n",
       "      <td>918.665696</td>\n",
       "      <td>-16.716457</td>\n",
       "      <td>12.347887</td>\n",
       "      <td>POINT (-16.716456507935607 12.34788723564788)</td>\n",
       "      <td>12.0</td>\n",
       "      <td>-16.722870</td>\n",
       "      <td>12.353291</td>\n",
       "      <td>POINT (-16.7228695 12.3532914)</td>\n",
       "      <td>18.0</td>\n",
       "      <td>3.796197</td>\n",
       "      <td>14.519779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>{D03C2B85-5F35-4EE8-8346-B83494628F26}</td>\n",
       "      <td>7761872847</td>\n",
       "      <td>952.759215</td>\n",
       "      <td>-16.713855</td>\n",
       "      <td>12.350881</td>\n",
       "      <td>POINT (-16.713855008830738 12.350880992129111)</td>\n",
       "      <td>7.0</td>\n",
       "      <td>-16.718793</td>\n",
       "      <td>12.357995</td>\n",
       "      <td>POINT (-16.7187927 12.3579947)</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3.796197</td>\n",
       "      <td>15.058638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>{5EAFF1C3-6EE5-4F96-99FC-78F924454480}</td>\n",
       "      <td>7761872847</td>\n",
       "      <td>1923.779554</td>\n",
       "      <td>-16.701275</td>\n",
       "      <td>12.355585</td>\n",
       "      <td>POINT (-16.701275174874546 12.355585269999269)</td>\n",
       "      <td>7.0</td>\n",
       "      <td>-16.718793</td>\n",
       "      <td>12.357995</td>\n",
       "      <td>POINT (-16.7187927 12.3579947)</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3.796197</td>\n",
       "      <td>30.405894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>{1D6A9E17-0D49-446D-A23B-7A47B155DC64}</td>\n",
       "      <td>7761872847</td>\n",
       "      <td>2181.254121</td>\n",
       "      <td>-16.698774</td>\n",
       "      <td>12.356804</td>\n",
       "      <td>POINT (-16.698773736706396 12.356804484409668)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-16.718793</td>\n",
       "      <td>12.357995</td>\n",
       "      <td>POINT (-16.7187927 12.3579947)</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3.796197</td>\n",
       "      <td>34.475355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125881</th>\n",
       "      <td>125881</td>\n",
       "      <td>125881</td>\n",
       "      <td>{5555A010-36B2-47D2-96C4-BDD1E59111ED}</td>\n",
       "      <td>8592243241</td>\n",
       "      <td>5089.086102</td>\n",
       "      <td>-14.397828</td>\n",
       "      <td>16.394143</td>\n",
       "      <td>POINT (-14.397827933065358 16.394142941310925)</td>\n",
       "      <td>24.0</td>\n",
       "      <td>-14.424516</td>\n",
       "      <td>16.432258</td>\n",
       "      <td>POINT (-14.4245157 16.4322581)</td>\n",
       "      <td>22.0</td>\n",
       "      <td>3.796198</td>\n",
       "      <td>80.434475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125882</th>\n",
       "      <td>125882</td>\n",
       "      <td>125882</td>\n",
       "      <td>{20205A44-8B9D-4FCE-B14C-53826594DB5A}</td>\n",
       "      <td>8592243457</td>\n",
       "      <td>4062.119008</td>\n",
       "      <td>-14.397473</td>\n",
       "      <td>16.405677</td>\n",
       "      <td>POINT (-14.397473236932905 16.405676938062538)</td>\n",
       "      <td>23.0</td>\n",
       "      <td>-14.420648</td>\n",
       "      <td>16.434798</td>\n",
       "      <td>POINT (-14.4206477 16.4347983)</td>\n",
       "      <td>18.0</td>\n",
       "      <td>3.796198</td>\n",
       "      <td>64.202962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125883</th>\n",
       "      <td>125883</td>\n",
       "      <td>125883</td>\n",
       "      <td>{AC6A169C-FD0E-4DF6-BDAB-B69FBD04BFAF}</td>\n",
       "      <td>8592243457</td>\n",
       "      <td>4008.851333</td>\n",
       "      <td>-14.400364</td>\n",
       "      <td>16.404303</td>\n",
       "      <td>POINT (-14.400364192239715 16.404303134272737)</td>\n",
       "      <td>24.0</td>\n",
       "      <td>-14.420648</td>\n",
       "      <td>16.434798</td>\n",
       "      <td>POINT (-14.4206477 16.4347983)</td>\n",
       "      <td>18.0</td>\n",
       "      <td>3.796198</td>\n",
       "      <td>63.361051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125884</th>\n",
       "      <td>125884</td>\n",
       "      <td>125884</td>\n",
       "      <td>{51593C65-B268-4BA1-8212-E43232C021FF}</td>\n",
       "      <td>3646207611</td>\n",
       "      <td>1826.174300</td>\n",
       "      <td>-14.396244</td>\n",
       "      <td>16.497151</td>\n",
       "      <td>POINT (-14.396243884215123 16.49715066208162)</td>\n",
       "      <td>7.0</td>\n",
       "      <td>-14.412651</td>\n",
       "      <td>16.492467</td>\n",
       "      <td>POINT (-14.412651 16.4924672)</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3.796197</td>\n",
       "      <td>28.863214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125885</th>\n",
       "      <td>125885</td>\n",
       "      <td>125885</td>\n",
       "      <td>{05114E26-63E9-4384-9F9E-8533D8AE2F1F}</td>\n",
       "      <td>8538238600</td>\n",
       "      <td>840.588582</td>\n",
       "      <td>-14.395109</td>\n",
       "      <td>16.631548</td>\n",
       "      <td>POINT (-14.395109427617555 16.631548057253372)</td>\n",
       "      <td>14.0</td>\n",
       "      <td>-14.402797</td>\n",
       "      <td>16.629875</td>\n",
       "      <td>POINT (-14.4027973 16.6298748)</td>\n",
       "      <td>17.0</td>\n",
       "      <td>3.796197</td>\n",
       "      <td>13.285747</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>125886 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0     vid                                GlobalID  \\\n",
       "0                0       0  {ED2CCDD5-C78F-40B6-A18A-3A01B61A4998}   \n",
       "1                1       1  {372B104B-B208-4D14-84E2-8ABFD4D8C37A}   \n",
       "2                2       2  {D03C2B85-5F35-4EE8-8346-B83494628F26}   \n",
       "3                3       3  {5EAFF1C3-6EE5-4F96-99FC-78F924454480}   \n",
       "4                4       4  {1D6A9E17-0D49-446D-A23B-7A47B155DC64}   \n",
       "...            ...     ...                                     ...   \n",
       "125881      125881  125881  {5555A010-36B2-47D2-96C4-BDD1E59111ED}   \n",
       "125882      125882  125882  {20205A44-8B9D-4FCE-B14C-53826594DB5A}   \n",
       "125883      125883  125883  {AC6A169C-FD0E-4DF6-BDAB-B69FBD04BFAF}   \n",
       "125884      125884  125884  {51593C65-B268-4BA1-8212-E43232C021FF}   \n",
       "125885      125885  125885  {05114E26-63E9-4384-9F9E-8533D8AE2F1F}   \n",
       "\n",
       "                NN      NN_dist     X_haml     Y_haml  \\\n",
       "0       7761872879   396.520984 -16.721473  12.348636   \n",
       "1       7761872860   918.665696 -16.716457  12.347887   \n",
       "2       7761872847   952.759215 -16.713855  12.350881   \n",
       "3       7761872847  1923.779554 -16.701275  12.355585   \n",
       "4       7761872847  2181.254121 -16.698774  12.356804   \n",
       "...            ...          ...        ...        ...   \n",
       "125881  8592243241  5089.086102 -14.397828  16.394143   \n",
       "125882  8592243457  4062.119008 -14.397473  16.405677   \n",
       "125883  8592243457  4008.851333 -14.400364  16.404303   \n",
       "125884  3646207611  1826.174300 -14.396244  16.497151   \n",
       "125885  8538238600   840.588582 -14.395109  16.631548   \n",
       "\n",
       "                                             geom_haml  v_elev     X_road  \\\n",
       "0       POINT (-16.721473282454415 12.348636090165247)    13.0 -16.724557   \n",
       "1        POINT (-16.716456507935607 12.34788723564788)    12.0 -16.722870   \n",
       "2       POINT (-16.713855008830738 12.350880992129111)     7.0 -16.718793   \n",
       "3       POINT (-16.701275174874546 12.355585269999269)     7.0 -16.718793   \n",
       "4       POINT (-16.698773736706396 12.356804484409668)     5.0 -16.718793   \n",
       "...                                                ...     ...        ...   \n",
       "125881  POINT (-14.397827933065358 16.394142941310925)    24.0 -14.424516   \n",
       "125882  POINT (-14.397473236932905 16.405676938062538)    23.0 -14.420648   \n",
       "125883  POINT (-14.400364192239715 16.404303134272737)    24.0 -14.420648   \n",
       "125884   POINT (-14.396243884215123 16.49715066208162)     7.0 -14.412651   \n",
       "125885  POINT (-14.395109427617555 16.631548057253372)    14.0 -14.402797   \n",
       "\n",
       "           Y_road                       geom_road  node_elev  walkspeed  \\\n",
       "0       12.350548  POINT (-16.7245571 12.3505478)        6.0   3.796199   \n",
       "1       12.353291  POINT (-16.7228695 12.3532914)       18.0   3.796197   \n",
       "2       12.357995  POINT (-16.7187927 12.3579947)       14.0   3.796197   \n",
       "3       12.357995  POINT (-16.7187927 12.3579947)       14.0   3.796197   \n",
       "4       12.357995  POINT (-16.7187927 12.3579947)       14.0   3.796197   \n",
       "...           ...                             ...        ...        ...   \n",
       "125881  16.432258  POINT (-14.4245157 16.4322581)       22.0   3.796198   \n",
       "125882  16.434798  POINT (-14.4206477 16.4347983)       18.0   3.796198   \n",
       "125883  16.434798  POINT (-14.4206477 16.4347983)       18.0   3.796198   \n",
       "125884  16.492467   POINT (-14.412651 16.4924672)       12.0   3.796197   \n",
       "125885  16.629875  POINT (-14.4027973 16.6298748)       17.0   3.796197   \n",
       "\n",
       "        walk_time  \n",
       "0        6.267126  \n",
       "1       14.519779  \n",
       "2       15.058638  \n",
       "3       30.405894  \n",
       "4       34.475355  \n",
       "...           ...  \n",
       "125881  80.434475  \n",
       "125882  64.202962  \n",
       "125883  63.361051  \n",
       "125884  28.863214  \n",
       "125885  13.285747  \n",
       "\n",
       "[125886 rows x 15 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zwalk2 = os.path.join(out_pth, \"fromagriculture/zwalk.csv\") \n",
    "zwalk2 = pd.read_csv(zwalk2)\n",
    "zwalk2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>NN</th>\n",
       "      <th>HDurban1</th>\n",
       "      <th>HDurban2</th>\n",
       "      <th>HDurban3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>7761872879</td>\n",
       "      <td>62.713982</td>\n",
       "      <td>66.144367</td>\n",
       "      <td>199.650409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>7761872860</td>\n",
       "      <td>61.991537</td>\n",
       "      <td>65.421922</td>\n",
       "      <td>198.927964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>7761872847</td>\n",
       "      <td>60.942482</td>\n",
       "      <td>64.372867</td>\n",
       "      <td>197.878909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>8604836683</td>\n",
       "      <td>68.078912</td>\n",
       "      <td>69.841801</td>\n",
       "      <td>195.450304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>8604829828</td>\n",
       "      <td>73.671735</td>\n",
       "      <td>75.434624</td>\n",
       "      <td>201.043127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23103</th>\n",
       "      <td>23103</td>\n",
       "      <td>8449983186</td>\n",
       "      <td>60.225974</td>\n",
       "      <td>61.707741</td>\n",
       "      <td>67.705341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23104</th>\n",
       "      <td>23104</td>\n",
       "      <td>4072935008</td>\n",
       "      <td>86.344963</td>\n",
       "      <td>88.583453</td>\n",
       "      <td>103.728980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23105</th>\n",
       "      <td>23105</td>\n",
       "      <td>4072935012</td>\n",
       "      <td>86.912227</td>\n",
       "      <td>89.150717</td>\n",
       "      <td>104.296245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23106</th>\n",
       "      <td>23106</td>\n",
       "      <td>8558304561</td>\n",
       "      <td>103.968632</td>\n",
       "      <td>106.207122</td>\n",
       "      <td>121.352649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23107</th>\n",
       "      <td>23107</td>\n",
       "      <td>4072041221</td>\n",
       "      <td>64.787107</td>\n",
       "      <td>66.268874</td>\n",
       "      <td>72.266474</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>23108 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0          NN    HDurban1    HDurban2    HDurban3\n",
       "0               0  7761872879   62.713982   66.144367  199.650409\n",
       "1               1  7761872860   61.991537   65.421922  198.927964\n",
       "2               2  7761872847   60.942482   64.372867  197.878909\n",
       "3               3  8604836683   68.078912   69.841801  195.450304\n",
       "4               4  8604829828   73.671735   75.434624  201.043127\n",
       "...           ...         ...         ...         ...         ...\n",
       "23103       23103  8449983186   60.225974   61.707741   67.705341\n",
       "23104       23104  4072935008   86.344963   88.583453  103.728980\n",
       "23105       23105  4072935012   86.912227   89.150717  104.296245\n",
       "23106       23106  8558304561  103.968632  106.207122  121.352649\n",
       "23107       23107  4072041221   64.787107   66.268874   72.266474\n",
       "\n",
       "[23108 rows x 5 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "HDurban_all = os.path.join(out_pth, \"fromagriculture/HDurban_all.csv\") \n",
    "HDurban_all = pd.read_csv(HDurban_all)\n",
    "HDurban_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 23108 entries, 0 to 23107\n",
      "Data columns (total 5 columns):\n",
      " #   Column      Non-Null Count  Dtype  \n",
      "---  ------      --------------  -----  \n",
      " 0   Unnamed: 0  23108 non-null  int64  \n",
      " 1   NN          23108 non-null  int64  \n",
      " 2   HDurban1    23106 non-null  float64\n",
      " 3   HDurban2    23108 non-null  float64\n",
      " 4   HDurban3    23108 non-null  float64\n",
      "dtypes: float64(3), int64(2)\n",
      "memory usage: 902.8 KB\n"
     ]
    }
   ],
   "source": [
    "HDurban_all.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 125886 entries, 0 to 125885\n",
      "Data columns (total 15 columns):\n",
      " #   Column      Non-Null Count   Dtype  \n",
      "---  ------      --------------   -----  \n",
      " 0   Unnamed: 0  125886 non-null  int64  \n",
      " 1   vid         125886 non-null  int64  \n",
      " 2   GlobalID    125886 non-null  object \n",
      " 3   NN          125886 non-null  int64  \n",
      " 4   NN_dist     125886 non-null  float64\n",
      " 5   X_haml      125886 non-null  float64\n",
      " 6   Y_haml      125886 non-null  float64\n",
      " 7   geom_haml   125886 non-null  object \n",
      " 8   v_elev      125886 non-null  float64\n",
      " 9   X_road      125886 non-null  float64\n",
      " 10  Y_road      125886 non-null  float64\n",
      " 11  geom_road   125886 non-null  object \n",
      " 12  node_elev   125886 non-null  float64\n",
      " 13  walkspeed   125886 non-null  float64\n",
      " 14  walk_time   125886 non-null  float64\n",
      "dtypes: float64(9), int64(3), object(3)\n",
      "memory usage: 14.4+ MB\n"
     ]
    }
   ],
   "source": [
    "zwalk2.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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       "      <td>13.0</td>\n",
       "      <td>3.796198</td>\n",
       "      <td>75.721003</td>\n",
       "      <td>22791</td>\n",
       "      <td>120.182403</td>\n",
       "      <td>121.664170</td>\n",
       "      <td>127.661769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125873</th>\n",
       "      <td>125873</td>\n",
       "      <td>125873</td>\n",
       "      <td>{AA6AA810-F293-48CB-AE66-13BD2FCD815F}</td>\n",
       "      <td>3656931340</td>\n",
       "      <td>5163.686119</td>\n",
       "      <td>-15.171010</td>\n",
       "      <td>16.533655</td>\n",
       "      <td>POINT (-15.171009716029147 16.53365451996827)</td>\n",
       "      <td>6.0</td>\n",
       "      <td>-15.127291</td>\n",
       "      <td>16.513644</td>\n",
       "      <td>POINT (-15.1272914 16.5136439)</td>\n",
       "      <td>13.0</td>\n",
       "      <td>3.796197</td>\n",
       "      <td>81.613553</td>\n",
       "      <td>22791</td>\n",
       "      <td>120.182403</td>\n",
       "      <td>121.664170</td>\n",
       "      <td>127.661769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125874</th>\n",
       "      <td>125874</td>\n",
       "      <td>125874</td>\n",
       "      <td>{857B624B-6DA5-4040-ADF3-7941A19A0E9E}</td>\n",
       "      <td>3189050596</td>\n",
       "      <td>5287.490997</td>\n",
       "      <td>-15.170870</td>\n",
       "      <td>16.536702</td>\n",
       "      <td>POINT (-15.17086967388112 16.53670207037827)</td>\n",
       "      <td>9.0</td>\n",
       "      <td>-15.218727</td>\n",
       "      <td>16.524309</td>\n",
       "      <td>POINT (-15.218727 16.5243085)</td>\n",
       "      <td>18.0</td>\n",
       "      <td>3.796197</td>\n",
       "      <td>83.570326</td>\n",
       "      <td>22686</td>\n",
       "      <td>113.132390</td>\n",
       "      <td>114.614157</td>\n",
       "      <td>120.611756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125875</th>\n",
       "      <td>125875</td>\n",
       "      <td>125875</td>\n",
       "      <td>{F0DB9BB4-5591-4293-A62D-F68DC076FAE6}</td>\n",
       "      <td>9208004078</td>\n",
       "      <td>855.054399</td>\n",
       "      <td>-15.169493</td>\n",
       "      <td>16.586997</td>\n",
       "      <td>POINT (-15.1694931869767 16.586996681143003)</td>\n",
       "      <td>7.0</td>\n",
       "      <td>-15.163943</td>\n",
       "      <td>16.592574</td>\n",
       "      <td>POINT (-15.1639432 16.5925737)</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3.796197</td>\n",
       "      <td>13.514384</td>\n",
       "      <td>22709</td>\n",
       "      <td>204.205579</td>\n",
       "      <td>204.553403</td>\n",
       "      <td>210.175731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125876</th>\n",
       "      <td>125876</td>\n",
       "      <td>125876</td>\n",
       "      <td>{CA5F83E9-4C85-4A2F-91F0-E42B7903C516}</td>\n",
       "      <td>3189049419</td>\n",
       "      <td>6922.750615</td>\n",
       "      <td>-14.401258</td>\n",
       "      <td>16.218009</td>\n",
       "      <td>POINT (-14.401257782929113 16.218009044751938)</td>\n",
       "      <td>31.0</td>\n",
       "      <td>-14.441340</td>\n",
       "      <td>16.267171</td>\n",
       "      <td>POINT (-14.4413403 16.2671706)</td>\n",
       "      <td>32.0</td>\n",
       "      <td>3.796198</td>\n",
       "      <td>109.416074</td>\n",
       "      <td>22735</td>\n",
       "      <td>213.528235</td>\n",
       "      <td>215.010002</td>\n",
       "      <td>221.007601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125877</th>\n",
       "      <td>125877</td>\n",
       "      <td>125877</td>\n",
       "      <td>{4A71AAB9-4D9C-45A4-B294-EA9C539748F4}</td>\n",
       "      <td>3189049419</td>\n",
       "      <td>4374.351827</td>\n",
       "      <td>-14.400672</td>\n",
       "      <td>16.271706</td>\n",
       "      <td>POINT (-14.400672317786873 16.27170615518481)</td>\n",
       "      <td>29.0</td>\n",
       "      <td>-14.441340</td>\n",
       "      <td>16.267171</td>\n",
       "      <td>POINT (-14.4413403 16.2671706)</td>\n",
       "      <td>32.0</td>\n",
       "      <td>3.796198</td>\n",
       "      <td>69.137895</td>\n",
       "      <td>22735</td>\n",
       "      <td>213.528235</td>\n",
       "      <td>215.010002</td>\n",
       "      <td>221.007601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125878</th>\n",
       "      <td>125878</td>\n",
       "      <td>125878</td>\n",
       "      <td>{276DFF8C-4A15-403F-8E1D-A9096BED1055}</td>\n",
       "      <td>9207769335</td>\n",
       "      <td>7249.550324</td>\n",
       "      <td>-14.399123</td>\n",
       "      <td>16.362761</td>\n",
       "      <td>POINT (-14.399122684709159 16.36276072662924)</td>\n",
       "      <td>20.0</td>\n",
       "      <td>-14.332654</td>\n",
       "      <td>16.376055</td>\n",
       "      <td>POINT (-14.332654 16.3760546)</td>\n",
       "      <td>16.0</td>\n",
       "      <td>3.796198</td>\n",
       "      <td>114.581235</td>\n",
       "      <td>22762</td>\n",
       "      <td>193.167566</td>\n",
       "      <td>194.649333</td>\n",
       "      <td>200.646933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125879</th>\n",
       "      <td>125879</td>\n",
       "      <td>125879</td>\n",
       "      <td>{05FA26B0-DA3F-48C5-A1EC-317A3A17D7F6}</td>\n",
       "      <td>9207769335</td>\n",
       "      <td>7090.505620</td>\n",
       "      <td>-14.398304</td>\n",
       "      <td>16.366501</td>\n",
       "      <td>POINT (-14.39830384291748 16.36650107644219)</td>\n",
       "      <td>24.0</td>\n",
       "      <td>-14.332654</td>\n",
       "      <td>16.376055</td>\n",
       "      <td>POINT (-14.332654 16.3760546)</td>\n",
       "      <td>16.0</td>\n",
       "      <td>3.796198</td>\n",
       "      <td>112.067486</td>\n",
       "      <td>22762</td>\n",
       "      <td>193.167566</td>\n",
       "      <td>194.649333</td>\n",
       "      <td>200.646933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125880</th>\n",
       "      <td>125880</td>\n",
       "      <td>125880</td>\n",
       "      <td>{027B1F86-0224-49E6-A44F-25F159749D1B}</td>\n",
       "      <td>8592243241</td>\n",
       "      <td>6194.919942</td>\n",
       "      <td>-14.398653</td>\n",
       "      <td>16.382131</td>\n",
       "      <td>POINT (-14.398653102247746 16.38213054383877)</td>\n",
       "      <td>28.0</td>\n",
       "      <td>-14.424516</td>\n",
       "      <td>16.432258</td>\n",
       "      <td>POINT (-14.4245157 16.4322581)</td>\n",
       "      <td>22.0</td>\n",
       "      <td>3.796198</td>\n",
       "      <td>97.912497</td>\n",
       "      <td>22763</td>\n",
       "      <td>184.980367</td>\n",
       "      <td>186.462134</td>\n",
       "      <td>192.459734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125881</th>\n",
       "      <td>125881</td>\n",
       "      <td>125881</td>\n",
       "      <td>{5555A010-36B2-47D2-96C4-BDD1E59111ED}</td>\n",
       "      <td>8592243241</td>\n",
       "      <td>5089.086102</td>\n",
       "      <td>-14.397828</td>\n",
       "      <td>16.394143</td>\n",
       "      <td>POINT (-14.397827933065358 16.394142941310925)</td>\n",
       "      <td>24.0</td>\n",
       "      <td>-14.424516</td>\n",
       "      <td>16.432258</td>\n",
       "      <td>POINT (-14.4245157 16.4322581)</td>\n",
       "      <td>22.0</td>\n",
       "      <td>3.796198</td>\n",
       "      <td>80.434475</td>\n",
       "      <td>22763</td>\n",
       "      <td>184.980367</td>\n",
       "      <td>186.462134</td>\n",
       "      <td>192.459734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125882</th>\n",
       "      <td>125882</td>\n",
       "      <td>125882</td>\n",
       "      <td>{20205A44-8B9D-4FCE-B14C-53826594DB5A}</td>\n",
       "      <td>8592243457</td>\n",
       "      <td>4062.119008</td>\n",
       "      <td>-14.397473</td>\n",
       "      <td>16.405677</td>\n",
       "      <td>POINT (-14.397473236932905 16.405676938062538)</td>\n",
       "      <td>23.0</td>\n",
       "      <td>-14.420648</td>\n",
       "      <td>16.434798</td>\n",
       "      <td>POINT (-14.4206477 16.4347983)</td>\n",
       "      <td>18.0</td>\n",
       "      <td>3.796198</td>\n",
       "      <td>64.202962</td>\n",
       "      <td>22774</td>\n",
       "      <td>184.681609</td>\n",
       "      <td>186.163376</td>\n",
       "      <td>192.160976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125883</th>\n",
       "      <td>125883</td>\n",
       "      <td>125883</td>\n",
       "      <td>{AC6A169C-FD0E-4DF6-BDAB-B69FBD04BFAF}</td>\n",
       "      <td>8592243457</td>\n",
       "      <td>4008.851333</td>\n",
       "      <td>-14.400364</td>\n",
       "      <td>16.404303</td>\n",
       "      <td>POINT (-14.400364192239715 16.404303134272737)</td>\n",
       "      <td>24.0</td>\n",
       "      <td>-14.420648</td>\n",
       "      <td>16.434798</td>\n",
       "      <td>POINT (-14.4206477 16.4347983)</td>\n",
       "      <td>18.0</td>\n",
       "      <td>3.796198</td>\n",
       "      <td>63.361051</td>\n",
       "      <td>22774</td>\n",
       "      <td>184.681609</td>\n",
       "      <td>186.163376</td>\n",
       "      <td>192.160976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125884</th>\n",
       "      <td>125884</td>\n",
       "      <td>125884</td>\n",
       "      <td>{51593C65-B268-4BA1-8212-E43232C021FF}</td>\n",
       "      <td>3646207611</td>\n",
       "      <td>1826.174300</td>\n",
       "      <td>-14.396244</td>\n",
       "      <td>16.497151</td>\n",
       "      <td>POINT (-14.396243884215123 16.49715066208162)</td>\n",
       "      <td>7.0</td>\n",
       "      <td>-14.412651</td>\n",
       "      <td>16.492467</td>\n",
       "      <td>POINT (-14.412651 16.4924672)</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3.796197</td>\n",
       "      <td>28.863214</td>\n",
       "      <td>22809</td>\n",
       "      <td>180.888369</td>\n",
       "      <td>182.370136</td>\n",
       "      <td>188.367736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125885</th>\n",
       "      <td>125885</td>\n",
       "      <td>125885</td>\n",
       "      <td>{05114E26-63E9-4384-9F9E-8533D8AE2F1F}</td>\n",
       "      <td>8538238600</td>\n",
       "      <td>840.588582</td>\n",
       "      <td>-14.395109</td>\n",
       "      <td>16.631548</td>\n",
       "      <td>POINT (-14.395109427617555 16.631548057253372)</td>\n",
       "      <td>14.0</td>\n",
       "      <td>-14.402797</td>\n",
       "      <td>16.629875</td>\n",
       "      <td>POINT (-14.4027973 16.6298748)</td>\n",
       "      <td>17.0</td>\n",
       "      <td>3.796197</td>\n",
       "      <td>13.285747</td>\n",
       "      <td>22935</td>\n",
       "      <td>196.227115</td>\n",
       "      <td>197.708882</td>\n",
       "      <td>203.706481</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0_x     vid                                GlobalID  \\\n",
       "125856        125856  125856  {22551739-F746-4C42-9CFA-918DA861DAE8}   \n",
       "125857        125857  125857  {A016A46D-7DEB-4516-85C3-D734CE32BB08}   \n",
       "125858        125858  125858  {0B17D0D9-24E9-45D6-A040-CE0BCAE1EBC5}   \n",
       "125859        125859  125859  {7BC3CDC3-F0F8-4864-A337-F26AE75A09EB}   \n",
       "125860        125860  125860  {34ED2616-7D64-45E9-8316-14E18D96BB3F}   \n",
       "125861        125861  125861  {6F416481-5D08-4A91-8986-33373551EA6F}   \n",
       "125862        125862  125862  {CA24AA7D-190F-42AF-9E2B-B4B99417510D}   \n",
       "125863        125863  125863  {E5BA361E-3599-4418-8957-1307399E23CB}   \n",
       "125864        125864  125864  {CFAB5FBB-E2E7-4E9B-85C0-2188C61DB227}   \n",
       "125865        125865  125865  {2A8F9A50-0609-48EF-A025-F4AC1D8860E6}   \n",
       "125866        125866  125866  {4BFF3246-F9EB-4051-8295-8FDF12F16FF6}   \n",
       "125867        125867  125867  {38882358-0C7F-4E93-9631-B8E81ABEDB90}   \n",
       "125868        125868  125868  {7BE065E8-84AF-41E8-9502-B638D6514525}   \n",
       "125869        125869  125869  {0D0DAAD9-DE3F-4063-B357-3A524CB2DAD9}   \n",
       "125870        125870  125870  {1AC212E3-ACC3-4575-A141-B1D6AFC41E09}   \n",
       "125871        125871  125871  {E43FA716-1B5A-4A0A-975B-D06BE6DD2454}   \n",
       "125872        125872  125872  {5C74F72E-6F61-4E55-96F6-C1C76FCFF200}   \n",
       "125873        125873  125873  {AA6AA810-F293-48CB-AE66-13BD2FCD815F}   \n",
       "125874        125874  125874  {857B624B-6DA5-4040-ADF3-7941A19A0E9E}   \n",
       "125875        125875  125875  {F0DB9BB4-5591-4293-A62D-F68DC076FAE6}   \n",
       "125876        125876  125876  {CA5F83E9-4C85-4A2F-91F0-E42B7903C516}   \n",
       "125877        125877  125877  {4A71AAB9-4D9C-45A4-B294-EA9C539748F4}   \n",
       "125878        125878  125878  {276DFF8C-4A15-403F-8E1D-A9096BED1055}   \n",
       "125879        125879  125879  {05FA26B0-DA3F-48C5-A1EC-317A3A17D7F6}   \n",
       "125880        125880  125880  {027B1F86-0224-49E6-A44F-25F159749D1B}   \n",
       "125881        125881  125881  {5555A010-36B2-47D2-96C4-BDD1E59111ED}   \n",
       "125882        125882  125882  {20205A44-8B9D-4FCE-B14C-53826594DB5A}   \n",
       "125883        125883  125883  {AC6A169C-FD0E-4DF6-BDAB-B69FBD04BFAF}   \n",
       "125884        125884  125884  {51593C65-B268-4BA1-8212-E43232C021FF}   \n",
       "125885        125885  125885  {05114E26-63E9-4384-9F9E-8533D8AE2F1F}   \n",
       "\n",
       "                NN       NN_dist     X_haml     Y_haml  \\\n",
       "125856  9041943742   3728.065735 -13.634542  15.748839   \n",
       "125857  1987817404   6756.790720 -13.632385  15.908039   \n",
       "125858  1987817404   6783.427144 -13.631616  15.909771   \n",
       "125859  3650030910   3534.224026 -13.629271  16.074080   \n",
       "125860  3650030910   3335.205126 -13.628169  16.075765   \n",
       "125861  9207762351   2928.681591 -14.312926  16.129799   \n",
       "125862  9207762351   2994.402598 -14.310434  16.129016   \n",
       "125863  9207762257   3222.986418 -14.285924  16.128193   \n",
       "125864  6128872306   6138.643077 -14.133517  16.126855   \n",
       "125865  6457408822   6651.716250 -14.022600  16.124635   \n",
       "125866  9207632658   2726.975017 -13.830473  16.121126   \n",
       "125867  4072041221    727.981836 -15.951347  16.200931   \n",
       "125868  5863612507    771.576796 -15.951585  16.202397   \n",
       "125869  5863612507    232.370315 -15.951187  16.210071   \n",
       "125870  5531975954    259.798004 -15.950313  16.212671   \n",
       "125871  3656977231  11526.719796 -15.174300  16.404790   \n",
       "125872  3656931340   4790.864817 -15.171234  16.522518   \n",
       "125873  3656931340   5163.686119 -15.171010  16.533655   \n",
       "125874  3189050596   5287.490997 -15.170870  16.536702   \n",
       "125875  9208004078    855.054399 -15.169493  16.586997   \n",
       "125876  3189049419   6922.750615 -14.401258  16.218009   \n",
       "125877  3189049419   4374.351827 -14.400672  16.271706   \n",
       "125878  9207769335   7249.550324 -14.399123  16.362761   \n",
       "125879  9207769335   7090.505620 -14.398304  16.366501   \n",
       "125880  8592243241   6194.919942 -14.398653  16.382131   \n",
       "125881  8592243241   5089.086102 -14.397828  16.394143   \n",
       "125882  8592243457   4062.119008 -14.397473  16.405677   \n",
       "125883  8592243457   4008.851333 -14.400364  16.404303   \n",
       "125884  3646207611   1826.174300 -14.396244  16.497151   \n",
       "125885  8538238600    840.588582 -14.395109  16.631548   \n",
       "\n",
       "                                             geom_haml  v_elev     X_road  \\\n",
       "125856  POINT (-13.634542240843889 15.748839239773597)    76.0 -13.658344   \n",
       "125857  POINT (-13.632384905651481 15.908038898553485)    72.0 -13.577587   \n",
       "125858  POINT (-13.631615806842289 15.909770584818125)    72.0 -13.577587   \n",
       "125859  POINT (-13.629271016877984 16.074080435238983)    12.0 -13.624898   \n",
       "125860  POINT (-13.628169393420567 16.075764507281782)    13.0 -13.624898   \n",
       "125861  POINT (-14.312925975367385 16.129798701531637)    40.0 -14.326172   \n",
       "125862    POINT (-14.310434450218114 16.1290157817221)    40.0 -14.326172   \n",
       "125863  POINT (-14.285923703058417 16.128193206058107)    43.0 -14.268569   \n",
       "125864  POINT (-14.133517144961344 16.126854804761635)    38.0 -14.106423   \n",
       "125865   POINT (-14.022600038102192 16.12463463543429)    31.0 -13.963910   \n",
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       "125885  POINT (-14.395109427617555 16.631548057253372)    14.0 -14.402797   \n",
       "\n",
       "           Y_road                       geom_road  node_elev  walkspeed  \\\n",
       "125856  15.773416  POINT (-13.6583444 15.7734165)       51.0   3.796198   \n",
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       "125864  16.175776  POINT (-14.1064229 16.1757757)       30.0   3.796198   \n",
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       "125870  16.213055  POINT (-15.9479155 16.2130548)        9.0   3.796194   \n",
       "125871  16.500739   POINT (-15.216413 16.5007394)       26.0   3.796198   \n",
       "125872  16.513644  POINT (-15.1272914 16.5136439)       13.0   3.796198   \n",
       "125873  16.513644  POINT (-15.1272914 16.5136439)       13.0   3.796197   \n",
       "125874  16.524309   POINT (-15.218727 16.5243085)       18.0   3.796197   \n",
       "125875  16.592574  POINT (-15.1639432 16.5925737)       12.0   3.796197   \n",
       "125876  16.267171  POINT (-14.4413403 16.2671706)       32.0   3.796198   \n",
       "125877  16.267171  POINT (-14.4413403 16.2671706)       32.0   3.796198   \n",
       "125878  16.376055   POINT (-14.332654 16.3760546)       16.0   3.796198   \n",
       "125879  16.376055   POINT (-14.332654 16.3760546)       16.0   3.796198   \n",
       "125880  16.432258  POINT (-14.4245157 16.4322581)       22.0   3.796198   \n",
       "125881  16.432258  POINT (-14.4245157 16.4322581)       22.0   3.796198   \n",
       "125882  16.434798  POINT (-14.4206477 16.4347983)       18.0   3.796198   \n",
       "125883  16.434798  POINT (-14.4206477 16.4347983)       18.0   3.796198   \n",
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       "125885  16.629875  POINT (-14.4027973 16.6298748)       17.0   3.796197   \n",
       "\n",
       "         walk_time  Unnamed: 0_y    HDurban1    HDurban2    HDurban3  \n",
       "125856   58.923147         21423  271.574996  273.084994  275.002987  \n",
       "125857  106.793020         21687  251.001380  252.511378  254.429371  \n",
       "125858  107.214016         21687  251.001380  252.511378  254.429371  \n",
       "125859   55.859434         21503  265.165442  266.647209  272.644808  \n",
       "125860   52.713882         21503  265.165442  266.647209  272.644808  \n",
       "125861   46.288661         21534  238.731555  240.213322  246.210922  \n",
       "125862   47.327400         21534  238.731555  240.213322  246.210922  \n",
       "125863   50.940231         21533  230.756438  232.238205  238.235805  \n",
       "125864   97.023024         21531  224.681084  226.162851  232.160451  \n",
       "125865  105.132296         21527  230.553613  232.035380  238.032980  \n",
       "125866   43.100628         21536  245.365971  246.847738  252.845338  \n",
       "125867   11.505961         23107   64.787107   66.268874   72.266474  \n",
       "125868   12.194994         22079   60.023681   61.505448   67.503048  \n",
       "125869    3.672681         22079   60.023681   61.505448   67.503048  \n",
       "125870    4.106186         22096   59.449192   60.930959   66.928559  \n",
       "125871  182.183134         22536  116.252233  117.734000  123.731600  \n",
       "125872   75.721003         22791  120.182403  121.664170  127.661769  \n",
       "125873   81.613553         22791  120.182403  121.664170  127.661769  \n",
       "125874   83.570326         22686  113.132390  114.614157  120.611756  \n",
       "125875   13.514384         22709  204.205579  204.553403  210.175731  \n",
       "125876  109.416074         22735  213.528235  215.010002  221.007601  \n",
       "125877   69.137895         22735  213.528235  215.010002  221.007601  \n",
       "125878  114.581235         22762  193.167566  194.649333  200.646933  \n",
       "125879  112.067486         22762  193.167566  194.649333  200.646933  \n",
       "125880   97.912497         22763  184.980367  186.462134  192.459734  \n",
       "125881   80.434475         22763  184.980367  186.462134  192.459734  \n",
       "125882   64.202962         22774  184.681609  186.163376  192.160976  \n",
       "125883   63.361051         22774  184.681609  186.163376  192.160976  \n",
       "125884   28.863214         22809  180.888369  182.370136  188.367736  \n",
       "125885   13.285747         22935  196.227115  197.708882  203.706481  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zwalk_HDurban = zwalk2.merge(HDurban_all, how='left', left_on='NN', right_on='NN', sort=False)\n",
    "zwalk_HDurban.tail(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>125884</th>\n",
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       "      <td>8538238600</td>\n",
       "      <td>840.588582</td>\n",
       "      <td>-14.395109</td>\n",
       "      <td>16.631548</td>\n",
       "      <td>POINT (-14.395109427617555 16.631548057253372)</td>\n",
       "      <td>14.0</td>\n",
       "      <td>-14.402797</td>\n",
       "      <td>...</td>\n",
       "      <td>17.0</td>\n",
       "      <td>3.796197</td>\n",
       "      <td>13.285747</td>\n",
       "      <td>22935</td>\n",
       "      <td>196.227115</td>\n",
       "      <td>197.708882</td>\n",
       "      <td>203.706481</td>\n",
       "      <td>209.512861</td>\n",
       "      <td>210.994628</td>\n",
       "      <td>216.992228</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>125886 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0_x     vid                                GlobalID  \\\n",
       "0                  0       0  {ED2CCDD5-C78F-40B6-A18A-3A01B61A4998}   \n",
       "1                  1       1  {372B104B-B208-4D14-84E2-8ABFD4D8C37A}   \n",
       "2                  2       2  {D03C2B85-5F35-4EE8-8346-B83494628F26}   \n",
       "3                  3       3  {5EAFF1C3-6EE5-4F96-99FC-78F924454480}   \n",
       "4                  4       4  {1D6A9E17-0D49-446D-A23B-7A47B155DC64}   \n",
       "...              ...     ...                                     ...   \n",
       "125881        125881  125881  {5555A010-36B2-47D2-96C4-BDD1E59111ED}   \n",
       "125882        125882  125882  {20205A44-8B9D-4FCE-B14C-53826594DB5A}   \n",
       "125883        125883  125883  {AC6A169C-FD0E-4DF6-BDAB-B69FBD04BFAF}   \n",
       "125884        125884  125884  {51593C65-B268-4BA1-8212-E43232C021FF}   \n",
       "125885        125885  125885  {05114E26-63E9-4384-9F9E-8533D8AE2F1F}   \n",
       "\n",
       "                NN      NN_dist     X_haml     Y_haml  \\\n",
       "0       7761872879   396.520984 -16.721473  12.348636   \n",
       "1       7761872860   918.665696 -16.716457  12.347887   \n",
       "2       7761872847   952.759215 -16.713855  12.350881   \n",
       "3       7761872847  1923.779554 -16.701275  12.355585   \n",
       "4       7761872847  2181.254121 -16.698774  12.356804   \n",
       "...            ...          ...        ...        ...   \n",
       "125881  8592243241  5089.086102 -14.397828  16.394143   \n",
       "125882  8592243457  4062.119008 -14.397473  16.405677   \n",
       "125883  8592243457  4008.851333 -14.400364  16.404303   \n",
       "125884  3646207611  1826.174300 -14.396244  16.497151   \n",
       "125885  8538238600   840.588582 -14.395109  16.631548   \n",
       "\n",
       "                                             geom_haml  v_elev     X_road  \\\n",
       "0       POINT (-16.721473282454415 12.348636090165247)    13.0 -16.724557   \n",
       "1        POINT (-16.716456507935607 12.34788723564788)    12.0 -16.722870   \n",
       "2       POINT (-16.713855008830738 12.350880992129111)     7.0 -16.718793   \n",
       "3       POINT (-16.701275174874546 12.355585269999269)     7.0 -16.718793   \n",
       "4       POINT (-16.698773736706396 12.356804484409668)     5.0 -16.718793   \n",
       "...                                                ...     ...        ...   \n",
       "125881  POINT (-14.397827933065358 16.394142941310925)    24.0 -14.424516   \n",
       "125882  POINT (-14.397473236932905 16.405676938062538)    23.0 -14.420648   \n",
       "125883  POINT (-14.400364192239715 16.404303134272737)    24.0 -14.420648   \n",
       "125884   POINT (-14.396243884215123 16.49715066208162)     7.0 -14.412651   \n",
       "125885  POINT (-14.395109427617555 16.631548057253372)    14.0 -14.402797   \n",
       "\n",
       "        ...  node_elev walkspeed  walk_time  Unnamed: 0_y    HDurban1  \\\n",
       "0       ...        6.0  3.796199   6.267126             0   62.713982   \n",
       "1       ...       18.0  3.796197  14.519779             1   61.991537   \n",
       "2       ...       14.0  3.796197  15.058638             2   60.942482   \n",
       "3       ...       14.0  3.796197  30.405894             2   60.942482   \n",
       "4       ...       14.0  3.796197  34.475355             2   60.942482   \n",
       "...     ...        ...       ...        ...           ...         ...   \n",
       "125881  ...       22.0  3.796198  80.434475         22763  184.980367   \n",
       "125882  ...       18.0  3.796198  64.202962         22774  184.681609   \n",
       "125883  ...       18.0  3.796198  63.361051         22774  184.681609   \n",
       "125884  ...       12.0  3.796197  28.863214         22809  180.888369   \n",
       "125885  ...       17.0  3.796197  13.285747         22935  196.227115   \n",
       "\n",
       "          HDurban2    HDurban3  mm1HDurban  mm2HDurban  mm3HDurban  \n",
       "0        66.144367  199.650409   68.981109   72.411493  205.917536  \n",
       "1        65.421922  198.927964   76.511316   79.941701  213.447743  \n",
       "2        64.372867  197.878909   76.001120   79.431504  212.937547  \n",
       "3        64.372867  197.878909   91.348377   94.778761  228.284804  \n",
       "4        64.372867  197.878909   95.417837   98.848222  232.354264  \n",
       "...            ...         ...         ...         ...         ...  \n",
       "125881  186.462134  192.459734  265.414842  266.896609  272.894209  \n",
       "125882  186.163376  192.160976  248.884571  250.366338  256.363938  \n",
       "125883  186.163376  192.160976  248.042660  249.524427  255.522026  \n",
       "125884  182.370136  188.367736  209.751583  211.233350  217.230950  \n",
       "125885  197.708882  203.706481  209.512861  210.994628  216.992228  \n",
       "\n",
       "[125886 rows x 22 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zwalk_HDurban[\"mm1HDurban\"] = 0\n",
    "zwalk_HDurban[\"mm1HDurban\"] = zwalk_HDurban[\"walk_time\"] + zwalk_HDurban[\"HDurban1\"]\n",
    "zwalk_HDurban[\"mm2HDurban\"] = 0\n",
    "zwalk_HDurban[\"mm2HDurban\"] = zwalk_HDurban[\"walk_time\"] + zwalk_HDurban[\"HDurban2\"]\n",
    "zwalk_HDurban[\"mm3HDurban\"] = 0\n",
    "zwalk_HDurban[\"mm3HDurban\"] = zwalk_HDurban[\"walk_time\"] + zwalk_HDurban[\"HDurban3\"]\n",
    "zwalk_HDurban"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "zwalk_HDurban.to_csv(os.path.join(out_pth, 'fromagriculture/fromagriculture_multimodal_HDurban.csv'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### End of script. Load into QGIS or Arc and visualize at 10 min intervals. \n",
    "QML file for symbology in QGIS:\n",
    "R:\\GEOGlobal\\Design\\symb_traveltimes_10min.qml"
   ]
  }
 ],
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