{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 20 Working with Web Feature Services\n",
    "\n",
    "In computing, the Open Geospatial Consortium Web Feature Service (WFS) Interface Standard provides an interface allowing requests for geographical features across the web using platform-independent calls. One can think of geographical features as the \"source code\" behind a map, whereas the WMS interface or online tiled mapping portals like Google Maps return only an image, which end-users cannot edit or spatially analyze. The XML-based GML furnishes the default payload-encoding for transporting geographic features, but other formats like shapefiles can also serve for transport. \n",
    "\n",
    "Source: https://en.wikipedia.org/wiki/Web_Feature_Service\n",
    "\n",
    "\n",
    "<img src=\"../images/tutorial20_cover.png\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set File Paths and download Tutorial Data\n",
    "\n",
    "If you downloaded the latest `GemGIS` version from the Github repository, append the path so that the package can be imported successfully. Otherwise, it is recommended to install `GemGIS` via `pip install gemgis` and import `GemGIS` using `import gemgis as gg`. In addition, the file path to the folder where the data is being stored is set. The tutorial data is downloaded using Pooch (https://www.fatiando.org/pooch/latest/index.html) and stored in the specified folder. Use `pip install pooch` if Pooch is not installed on your system yet."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-17T11:17:36.916455Z",
     "start_time": "2021-03-17T11:17:34.561592Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING (theano.configdefaults): g++ not available, if using conda: `conda install m2w64-toolchain`\n",
      "C:\\Users\\ale93371\\Anaconda3\\envs\\test_gempy\\lib\\site-packages\\theano\\configdefaults.py:560: UserWarning: DeprecationWarning: there is no c++ compiler.This is deprecated and with Theano 0.11 a c++ compiler will be mandatory\n",
      "  warnings.warn(\"DeprecationWarning: there is no c++ compiler.\"\n",
      "WARNING (theano.configdefaults): g++ not detected ! Theano will be unable to execute optimized C-implementations (for both CPU and GPU) and will default to Python implementations. Performance will be severely degraded. To remove this warning, set Theano flags cxx to an empty string.\n",
      "WARNING (theano.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
     ]
    }
   ],
   "source": [
    "import gemgis as gg\n",
    "\n",
    "file_path ='data/20_working_with_web_feature_services/'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading the WFS Service\n",
    "\n",
    "For this example, we are downloading a WFS Service provided by the \n",
    "[Landesamt für Bergbau, Energie und Geologie - Niedersachsen](#https://www.lbeg.niedersachsen.de/startseite/). It contains Polygon, Line and Point data about seismic surveys and wells in Northern Germany. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-30T12:46:35.207875Z",
     "start_time": "2020-12-30T12:46:33.939061Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<owslib.feature.wfs100.WebFeatureService_1_0_0 at 0x19260e21340>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wfs = gg.web.load_wfs(\"https://nibis.lbeg.de/net3/public/ogc.ashx?NodeId=476&Service=WFS&\")\n",
    "wfs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:04.756528Z",
     "start_time": "2020-12-10T17:20:04.745526Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "owslib.feature.wfs100.WebFeatureService_1_0_0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(wfs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the version of the WFS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:04.772531Z",
     "start_time": "2020-12-10T17:20:04.760530Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.0.0'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wfs.version"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the version of the WFS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:04.788533Z",
     "start_time": "2020-12-10T17:20:04.777533Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.0.0'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wfs.identification.version"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the identification type of the WFS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:04.804536Z",
     "start_time": "2020-12-10T17:20:04.792539Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Geophysik und Tiefohrungen'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wfs.identification.type"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the title of the WFS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:04.820540Z",
     "start_time": "2020-12-10T17:20:04.809539Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Geophysik und Tiefohrungen'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wfs.identification.title"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the abstract of the WFS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:04.835546Z",
     "start_time": "2020-12-10T17:20:04.824544Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Geophysik und Tiefohrungen'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wfs.identification.abstract"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the contents of the WFS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:04.851573Z",
     "start_time": "2020-12-10T17:20:04.838546Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['iwan:L383']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(wfs.contents)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the title of the WFS layer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:04.867589Z",
     "start_time": "2020-12-10T17:20:04.854578Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Gravimetrie'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wfs['iwan:L383'].title"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the bounding box of the WFS layer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:04.883573Z",
     "start_time": "2020-12-10T17:20:04.870576Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5.395175801132899, 47.16510247399335, 17.002272548448747, 54.85398076006902)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wfs['iwan:L383'].boundingBoxWGS84"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the operations for the WFS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:04.898589Z",
     "start_time": "2020-12-10T17:20:04.886578Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['GetCapabilities', 'DescribeFeatureType', 'GetFeature']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[op.name for op in wfs.operations]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the format for getting the feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:04.914581Z",
     "start_time": "2020-12-10T17:20:04.901578Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['{http://www.opengis.net/wfs}GML2']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wfs.getOperationByName('GetFeature').formatOptions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the format for describing the feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:04.930594Z",
     "start_time": "2020-12-10T17:20:04.917581Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wfs.getOperationByName('DescribeFeatureType').formatOptions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the format for getting the capabilities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:04.946636Z",
     "start_time": "2020-12-10T17:20:04.933584Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wfs.getOperationByName('GetCapabilities').formatOptions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Requesting data from the WFS\n",
    "\n",
    "The features can be loaded with the function ``load_as_gpd(..)``."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:14.375952Z",
     "start_time": "2020-12-10T17:20:04.949636Z"
    }
   },
   "outputs": [],
   "source": [
    "feature = gg.web.load_as_gpd(\"https://nibis.lbeg.de/net3/public/ogc.ashx?NodeId=476&Service=WFS&\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking the head of the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:14.454768Z",
     "start_time": "2020-12-10T17:20:14.379938Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gml_id</th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>ID</th>\n",
       "      <th>SURVEYNAME</th>\n",
       "      <th>ARCHIV</th>\n",
       "      <th>MESSJAHR</th>\n",
       "      <th>OPERATOR</th>\n",
       "      <th>OP_NACHFOL</th>\n",
       "      <th>MESSFIRMA</th>\n",
       "      <th>MESSPUNKTE</th>\n",
       "      <th>UP_DATE</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1541</td>\n",
       "      <td>1541</td>\n",
       "      <td>112</td>\n",
       "      <td>Jemgum 2007</td>\n",
       "      <td>0127494</td>\n",
       "      <td>2007</td>\n",
       "      <td>GdF Produktion Exploration Deutschland GmbH</td>\n",
       "      <td>Neptune Energy Deutschland GmbH</td>\n",
       "      <td>Geophysik und Geotechnik Leipzig GmbH</td>\n",
       "      <td>1340</td>\n",
       "      <td>2020-01-20T00:00:00+01:00</td>\n",
       "      <td>MULTIPOLYGON (((32395246.839 5907777.660, 3239...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1542</td>\n",
       "      <td>1542</td>\n",
       "      <td>111</td>\n",
       "      <td>Sagermeer 2005</td>\n",
       "      <td>0125831</td>\n",
       "      <td>2005</td>\n",
       "      <td>ExxonMobil Production Deutschland GmbH</td>\n",
       "      <td>ExxonMobil Production Deutschland GmbH</td>\n",
       "      <td>Comp. Generale Geophysique</td>\n",
       "      <td>2803</td>\n",
       "      <td>2020-01-20T00:00:00+01:00</td>\n",
       "      <td>MULTIPOLYGON (((32446717.522 5856710.088, 3244...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1543</td>\n",
       "      <td>1543</td>\n",
       "      <td>120</td>\n",
       "      <td>Hümmling 2013</td>\n",
       "      <td>0131520</td>\n",
       "      <td>2013</td>\n",
       "      <td>GDF SUEZ E&amp;P DEUTSCHLAND GMBH</td>\n",
       "      <td>Neptune Energy Deutschland GmbH</td>\n",
       "      <td>Deutsche Montan Technologie GmbH</td>\n",
       "      <td>342</td>\n",
       "      <td>2020-01-20T00:00:00+01:00</td>\n",
       "      <td>MULTIPOLYGON (((32416592.825 5852885.544, 3241...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1544</td>\n",
       "      <td>1544</td>\n",
       "      <td>49</td>\n",
       "      <td>Rotenburg/Wümme (1984)</td>\n",
       "      <td>0112162</td>\n",
       "      <td>1984</td>\n",
       "      <td>Deutsche Texaco AG Aufschluss und Gew.</td>\n",
       "      <td>Wintershall Dea Deutschland AG</td>\n",
       "      <td>Prakla Seismos</td>\n",
       "      <td>2184</td>\n",
       "      <td>2020-01-20T00:00:00+01:00</td>\n",
       "      <td>POLYGON ((32545955.921 5896473.525, 32544536.2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1545</td>\n",
       "      <td>1545</td>\n",
       "      <td>102</td>\n",
       "      <td>Odisheim 1989/90</td>\n",
       "      <td>0112092</td>\n",
       "      <td>1989</td>\n",
       "      <td>BEB Erdgas und Erdöl GmbH</td>\n",
       "      <td>BEB Erdgas und Erdöl GmbH &amp; Co. KG</td>\n",
       "      <td>Prakla Seismos</td>\n",
       "      <td>2824</td>\n",
       "      <td>2020-01-20T00:00:00+01:00</td>\n",
       "      <td>POLYGON ((32504255.640 5967591.298, 32503387.8...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  gml_id  OBJECTID   ID              SURVEYNAME   ARCHIV  MESSJAHR  \\\n",
       "0   1541      1541  112             Jemgum 2007  0127494      2007   \n",
       "1   1542      1542  111          Sagermeer 2005  0125831      2005   \n",
       "2   1543      1543  120           Hümmling 2013  0131520      2013   \n",
       "3   1544      1544   49  Rotenburg/Wümme (1984)  0112162      1984   \n",
       "4   1545      1545  102        Odisheim 1989/90  0112092      1989   \n",
       "\n",
       "                                      OPERATOR  \\\n",
       "0  GdF Produktion Exploration Deutschland GmbH   \n",
       "1       ExxonMobil Production Deutschland GmbH   \n",
       "2                GDF SUEZ E&P DEUTSCHLAND GMBH   \n",
       "3       Deutsche Texaco AG Aufschluss und Gew.   \n",
       "4                    BEB Erdgas und Erdöl GmbH   \n",
       "\n",
       "                               OP_NACHFOL  \\\n",
       "0         Neptune Energy Deutschland GmbH   \n",
       "1  ExxonMobil Production Deutschland GmbH   \n",
       "2         Neptune Energy Deutschland GmbH   \n",
       "3          Wintershall Dea Deutschland AG   \n",
       "4      BEB Erdgas und Erdöl GmbH & Co. KG   \n",
       "\n",
       "                               MESSFIRMA  MESSPUNKTE  \\\n",
       "0  Geophysik und Geotechnik Leipzig GmbH        1340   \n",
       "1             Comp. Generale Geophysique        2803   \n",
       "2       Deutsche Montan Technologie GmbH         342   \n",
       "3                         Prakla Seismos        2184   \n",
       "4                         Prakla Seismos        2824   \n",
       "\n",
       "                     UP_DATE  \\\n",
       "0  2020-01-20T00:00:00+01:00   \n",
       "1  2020-01-20T00:00:00+01:00   \n",
       "2  2020-01-20T00:00:00+01:00   \n",
       "3  2020-01-20T00:00:00+01:00   \n",
       "4  2020-01-20T00:00:00+01:00   \n",
       "\n",
       "                                            geometry  \n",
       "0  MULTIPOLYGON (((32395246.839 5907777.660, 3239...  \n",
       "1  MULTIPOLYGON (((32446717.522 5856710.088, 3244...  \n",
       "2  MULTIPOLYGON (((32416592.825 5852885.544, 3241...  \n",
       "3  POLYGON ((32545955.921 5896473.525, 32544536.2...  \n",
       "4  POLYGON ((32504255.640 5967591.298, 32503387.8...  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plotting the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-10T17:20:15.377494Z",
     "start_time": "2020-12-10T17:20:14.459772Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 748.8x514.8 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "feature.plot()\n",
    "plt.grid()"
   ]
  }
 ],
 "metadata": {
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}