Part2-NEON_and_Observatories_RESTAPI.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Use Case 2 - Part 2: Sites from NEON Web Services REST API (and LTER & GLEON)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- [Emilio Mayorga](https://github.com/emiliom), University of Washington\n",
    "- [WaterHackWeek](https://waterhackweek.github.io/) Cyberseminar\n",
    "- 2019-2-7\n",
    "- **Re-ran successfully by Emilio on 2/26/2020 using his `whwtimeseries_cso.yml` conda env file**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use the NEON REST API for illustrating a `requests`-based REST API access and parsing into Pandas DataFrames and GeoPandas GeoDataFrames, followed by visualization on an interactive Folium map together with nearby sites from the LTER and GLEON networks.\n",
    "\n",
    "**NEON documentation:**\n",
    "- NEON REST API: http://data.neonscience.org/data-api\n",
    "- [Useful REST API documentation, based on the R client](https://www.neonscience.org/neon-api-usage)\n",
    "- [REST API Jupyter Notebook Python example](https://nbviewer.jupyter.org/gist/jzollerneon/3d0519e1f26db80b755cc865ef218d58)\n",
    "- [NEON field sites](https://www.neonscience.org/field-sites) also available for download as csv at https://www.neonscience.org/field-sites/field-sites-map/list. This page shows [maps of the domains and sites.](https://www.neonscience.org/field-sites/types-neon-field-sites)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import json\n",
    "from io import StringIO\n",
    "import requests\n",
    "\n",
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "import shapely.geometry as shpgeom\n",
    "import matplotlib.pyplot as plt\n",
    "import folium"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "NEON REST API base url"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "neon_api_baseurl = \"http://data.neonscience.org/api/v0/\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get NEON site data using REST API"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`sites` is the REST API \"end point\". The API returns a JSON string."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "sites_response = requests.get(neon_api_baseurl + 'sites/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sites_json = sites_response.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['data'])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sites_json.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(list, 81)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(sites_json['data']), len(sites_json['data'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(dict,\n",
       " dict_keys(['siteDescription', 'siteLongitude', 'siteType', 'stateName', 'stateCode', 'siteLatitude', 'domainName', 'domainCode', 'siteCode', 'dataProducts', 'siteName']))"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(sites_json['data'][0]), sites_json['data'][0].keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "List all the individual ecological \"domains\" (names and codes), followed by a listing of sites found in the two domains of interest: 'Appalachians and Cumberland Plateau' and 'Ozarks Complex'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{('Appalachians and Cumberland Plateau', 'D07'),\n",
       " ('Atlantic Neotropical', 'D04'),\n",
       " ('Central Plains', 'D10'),\n",
       " ('Desert Southwest', 'D14'),\n",
       " ('Great Basin', 'D15'),\n",
       " ('Great Lakes', 'D05'),\n",
       " ('Mid-Atlantic', 'D02'),\n",
       " ('Northeast', 'D01'),\n",
       " ('Northern Plains', 'D09'),\n",
       " ('Northern Rockies', 'D12'),\n",
       " ('Ozarks Complex', 'D08'),\n",
       " ('Pacific Northwest', 'D16'),\n",
       " ('Pacific Southwest', 'D17'),\n",
       " ('Pacific Tropical', 'D20'),\n",
       " ('Prairie Peninsula', 'D06'),\n",
       " ('Southeast', 'D03'),\n",
       " ('Southern Plains', 'D11'),\n",
       " ('Southern Rockies and Colorado Plateau', 'D13'),\n",
       " ('Taiga', 'D19'),\n",
       " ('Tundra', 'D18')}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set([(s['domainName'], s['domainCode']) for s in sites_json['data']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "D08 Black Warrior River Site, RELOCATABLE: -87.798151, 32.541529\n",
      "D08 Dead Lake Site, RELOCATABLE: -87.803877, 32.541727\n",
      "D07 Great Smoky Mountains National Park Site, RELOCATABLE: -83.50195, 35.68896\n",
      "D07 LeConte Creek Site, RELOCATABLE: -83.50379, 35.690428\n",
      "D08 Lenoir Landing Site, RELOCATABLE: -88.161181, 31.853861\n",
      "D08 Mayfield Creek Site, CORE: -87.407688, 32.960365\n",
      "D07 Mountain Lake Biological Station Site, RELOCATABLE: -80.524847, 37.378314\n",
      "D07 Oak Ridge Site, CORE: -84.282588, 35.964128\n",
      "D08 Talladega National Forest Site, CORE: -87.393259, 32.95047\n",
      "D08 Tombigbee River Site, RELOCATABLE: -88.158872, 31.853431\n",
      "D07 Walker Branch Site, CORE: -84.279251, 35.957378\n"
     ]
    }
   ],
   "source": [
    "for s in sites_json['data']:\n",
    "    if s['domainName'] in ('Appalachians and Cumberland Plateau', 'Ozarks Complex'):\n",
    "        print(\"{} {}: {}, {}\".format(s['domainCode'], s['siteName'], \n",
    "                                     s['siteLongitude'], s['siteLatitude']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A sample of what the `dataProducts` dictionary chunk looks like:\n",
    "```json\n",
    "'dataProducts': [{'dataProductCode': 'DP1.10066.001',\n",
    "   'dataProductTitle': 'Root sampling (Megapit)',\n",
    "   'availableMonths': ['2015-06'],\n",
    "   'availableDataUrls': ['http://data.neonscience.org:80/api/v0/data/DP1.10066.001/ABBY/2015-06']},\n",
    "  {'dataProductCode': 'DP1.10023.001',\n",
    "   'dataProductTitle': 'Herbaceous clip harvest',\n",
    "   'availableMonths': ['2016-08', '2017-07', '2017-08', '2018-07', '2018-08'],\n",
    "   'availableDataUrls': ['http://data.neonscience.org:80/api/v0/data/DP1.10023.001/ABBY/2016-08',\n",
    "    'http://data.neonscience.org:80/api/v0/data/DP1.10023.001/ABBY/2017-07',\n",
    "    'http://data.neonscience.org:80/api/v0/data/DP1.10023.001/ABBY/2017-08',\n",
    "    'http://data.neonscience.org:80/api/v0/data/DP1.10023.001/ABBY/2018-07',\n",
    "    'http://data.neonscience.org:80/api/v0/data/DP1.10023.001/ABBY/2018-08']},\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ingest and examine selected NEON sites into a GeoDataFrame\n",
    "Then filter based on availability of desired aquatic [NEON Data Products](http://data.neonscience.org/data-product-catalog): dissolved oxygen (water quality), stream stage (water height) and stream discharge. The \"base\" data product codes are `DP1.20288`, `DP1.20016` and `DP4.00130`. Here's the documentation for one of them: http://data.neonscience.org/data-product-view?dpCode=DP1.20016.001"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "neon_sites_tn_allprods = [\n",
    "    s for s in sites_json['data']\n",
    "    if s['domainName'] in ('Appalachians and Cumberland Plateau', 'Ozarks Complex')\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(11, list)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(neon_sites_tn_allprods), type(neon_sites_tn_allprods)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create Pandas DataFrame from sites data in Python dictionary, then create a GeoPandas GeoDataFrame from DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "sites_df = pd.DataFrame.from_records([site for site in neon_sites_tn_allprods])\n",
    "sites_df.set_index('siteCode', drop=False, inplace=True)\n",
    "\n",
    "neon_sites_tn_allprods_gdf = gpd.GeoDataFrame(sites_df,\n",
    "                                          geometry=sites_df[['siteLongitude', 'siteLatitude']].apply(\n",
    "                                              shpgeom.Point, axis=1),\n",
    "                                          crs={'init': 'epsg:4326'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "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>dataProducts</th>\n",
       "      <th>domainCode</th>\n",
       "      <th>domainName</th>\n",
       "      <th>siteCode</th>\n",
       "      <th>siteDescription</th>\n",
       "      <th>siteLatitude</th>\n",
       "      <th>siteLongitude</th>\n",
       "      <th>siteName</th>\n",
       "      <th>siteType</th>\n",
       "      <th>stateCode</th>\n",
       "      <th>stateName</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>siteCode</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BLWA</th>\n",
       "      <td>[{'dataProductCode': 'DP1.20002.001', 'dataPro...</td>\n",
       "      <td>D08</td>\n",
       "      <td>Ozarks Complex</td>\n",
       "      <td>BLWA</td>\n",
       "      <td>Black Warrior River</td>\n",
       "      <td>32.541529</td>\n",
       "      <td>-87.798151</td>\n",
       "      <td>Black Warrior River Site, RELOCATABLE</td>\n",
       "      <td>RELOCATABLE</td>\n",
       "      <td>AL</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>POINT (-87.798151 32.541529)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DELA</th>\n",
       "      <td>[{'dataProductCode': 'DP1.00001.001', 'dataPro...</td>\n",
       "      <td>D08</td>\n",
       "      <td>Ozarks Complex</td>\n",
       "      <td>DELA</td>\n",
       "      <td>Dead Lake</td>\n",
       "      <td>32.541727</td>\n",
       "      <td>-87.803877</td>\n",
       "      <td>Dead Lake Site, RELOCATABLE</td>\n",
       "      <td>RELOCATABLE</td>\n",
       "      <td>AL</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>POINT (-87.803877 32.541727)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               dataProducts domainCode  \\\n",
       "siteCode                                                                 \n",
       "BLWA      [{'dataProductCode': 'DP1.20002.001', 'dataPro...        D08   \n",
       "DELA      [{'dataProductCode': 'DP1.00001.001', 'dataPro...        D08   \n",
       "\n",
       "              domainName siteCode      siteDescription  siteLatitude  \\\n",
       "siteCode                                                               \n",
       "BLWA      Ozarks Complex     BLWA  Black Warrior River     32.541529   \n",
       "DELA      Ozarks Complex     DELA            Dead Lake     32.541727   \n",
       "\n",
       "          siteLongitude                               siteName     siteType  \\\n",
       "siteCode                                                                      \n",
       "BLWA         -87.798151  Black Warrior River Site, RELOCATABLE  RELOCATABLE   \n",
       "DELA         -87.803877            Dead Lake Site, RELOCATABLE  RELOCATABLE   \n",
       "\n",
       "         stateCode stateName                      geometry  \n",
       "siteCode                                                    \n",
       "BLWA            AL   Alabama  POINT (-87.798151 32.541529)  \n",
       "DELA            AL   Alabama  POINT (-87.803877 32.541727)  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neon_sites_tn_allprods_gdf.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's examine some of the information for dataProducts (variables). Then we'll retain only the sites that have any of the three desired data products, and add some flags indicating whether each of the desired data products are found in the site."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'dataProductCode': 'DP1.20002.001',\n",
       " 'dataProductTitle': 'Land-water interface images',\n",
       " 'availableMonths': ['2018-10',\n",
       "  '2018-11',\n",
       "  '2018-12',\n",
       "  '2019-05',\n",
       "  '2019-06',\n",
       "  '2019-07',\n",
       "  '2019-08',\n",
       "  '2019-09',\n",
       "  '2019-10',\n",
       "  '2019-11',\n",
       "  '2019-12',\n",
       "  '2020-01',\n",
       "  '2020-02'],\n",
       " 'availableDataUrls': ['https://data.neonscience.org/api/v0/data/DP1.20002.001/BLWA/2018-10',\n",
       "  'https://data.neonscience.org/api/v0/data/DP1.20002.001/BLWA/2018-11',\n",
       "  'https://data.neonscience.org/api/v0/data/DP1.20002.001/BLWA/2018-12',\n",
       "  'https://data.neonscience.org/api/v0/data/DP1.20002.001/BLWA/2019-05',\n",
       "  'https://data.neonscience.org/api/v0/data/DP1.20002.001/BLWA/2019-06',\n",
       "  'https://data.neonscience.org/api/v0/data/DP1.20002.001/BLWA/2019-07',\n",
       "  'https://data.neonscience.org/api/v0/data/DP1.20002.001/BLWA/2019-08',\n",
       "  'https://data.neonscience.org/api/v0/data/DP1.20002.001/BLWA/2019-09',\n",
       "  'https://data.neonscience.org/api/v0/data/DP1.20002.001/BLWA/2019-10',\n",
       "  'https://data.neonscience.org/api/v0/data/DP1.20002.001/BLWA/2019-11',\n",
       "  'https://data.neonscience.org/api/v0/data/DP1.20002.001/BLWA/2019-12',\n",
       "  'https://data.neonscience.org/api/v0/data/DP1.20002.001/BLWA/2020-01',\n",
       "  'https://data.neonscience.org/api/v0/data/DP1.20002.001/BLWA/2020-02']}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neon_sites_tn_allprods_gdf.iloc[0]['dataProducts'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# What I'm flagging as \"oxygen\" is actually a broader \"water quality\" data product\n",
    "neon_sites_tn = []\n",
    "for s in neon_sites_tn_allprods[:]:\n",
    "    dataproductcodes = [dp['dataProductCode'] for dp in s['dataProducts']]\n",
    "    s['oxygen'] = True if 'DP1.20288.001' in dataproductcodes else False\n",
    "    s['discharge'] = True if 'DP4.00130.001' in dataproductcodes else False\n",
    "    s['stage'] = True if 'DP1.20016.001' in dataproductcodes else False\n",
    "    if s['oxygen'] or s['discharge'] or s['stage']:\n",
    "        neon_sites_tn.append(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(neon_sites_tn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "sites_df = pd.DataFrame.from_records([site for site in neon_sites_tn])\n",
    "sites_df.set_index('siteCode', drop=False, inplace=True)\n",
    "\n",
    "neon_sites_tn_gdf = gpd.GeoDataFrame(sites_df,\n",
    "                                   geometry=sites_df[['siteLongitude', 'siteLatitude']].apply(\n",
    "                                       shpgeom.Point, axis=1),\n",
    "                                    crs={'init': 'epsg:4326'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 216x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A quick geopandas plot, just as a check\n",
    "neon_sites_tn_gdf.plot(figsize=(3, 3));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get LTER sites and single GLEON site\n",
    "- [LTER](https://lternet.edu) Sites dataset: https://portal.edirepository.org/nis/mapbrowse?packageid=edi.138.3\n",
    "- [GLEON](http://gleon.org) site information for Kentucky Lake: http://gleon.org/lakes/kentucky-lake. GLEON doesn't offer a sites dataset or a convenient presentation of latitude and longitude coordinates, so I had to search around. The best resource was [this interactive map](http://gleon.org/members/lakes/map). The coordinates for Kentucky Lake are latitude 36.733533, longitude -88.11666"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "lter_sites_url = \"https://portal.edirepository.org/nis/dataviewer?packageid=edi.138.3&entityid=5e88b1508627d2618eadb56852a188f9\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "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>site_id_text</th>\n",
       "      <th>site_name</th>\n",
       "      <th>address1</th>\n",
       "      <th>address2</th>\n",
       "      <th>address3</th>\n",
       "      <th>address4</th>\n",
       "      <th>address5</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zip</th>\n",
       "      <th>country</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>network_name</th>\n",
       "      <th>elevation</th>\n",
       "      <th>ecosystem</th>\n",
       "      <th>latitude_comment</th>\n",
       "      <th>longitude_comment</th>\n",
       "      <th>elevation_comment</th>\n",
       "      <th>ecosystem_comment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AND</td>\n",
       "      <td>Andrews Forest LTER</td>\n",
       "      <td>Andrews Experimental Forest</td>\n",
       "      <td>P.O. Box 300</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Blue River</td>\n",
       "      <td>OR</td>\n",
       "      <td>97413</td>\n",
       "      <td>USA</td>\n",
       "      <td>44.212</td>\n",
       "      <td>-122.256</td>\n",
       "      <td>us</td>\n",
       "      <td>1020.0</td>\n",
       "      <td>Coniferous Forest</td>\n",
       "      <td>Data Source: LTER Site Characteristics Databas...</td>\n",
       "      <td>Data Source: LTER Site Characteristics Databas...</td>\n",
       "      <td>Data Source: Collins/Waide. class data.  2008....</td>\n",
       "      <td>Data Source: GreenLand, D., G. G. Goodin., R. ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  site_id_text            site_name                     address1  \\\n",
       "0          AND  Andrews Forest LTER  Andrews Experimental Forest   \n",
       "\n",
       "       address2 address3  address4  address5        city state    zip country  \\\n",
       "0  P.O. Box 300      NaN       NaN       NaN  Blue River    OR  97413     USA   \n",
       "\n",
       "   latitude  longitude network_name  elevation          ecosystem  \\\n",
       "0    44.212   -122.256           us     1020.0  Coniferous Forest   \n",
       "\n",
       "                                    latitude_comment  \\\n",
       "0  Data Source: LTER Site Characteristics Databas...   \n",
       "\n",
       "                                   longitude_comment  \\\n",
       "0  Data Source: LTER Site Characteristics Databas...   \n",
       "\n",
       "                                   elevation_comment  \\\n",
       "0  Data Source: Collins/Waide. class data.  2008....   \n",
       "\n",
       "                                   ecosystem_comment  \n",
       "0  Data Source: GreenLand, D., G. G. Goodin., R. ...  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r = requests.get(lter_sites_url)\n",
    "\n",
    "lter_sites_df = pd.read_csv(StringIO(r.text))\n",
    "lter_sites_df.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Map all sites with Folium\n",
    "From the three observation networks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "m = folium.Map(tiles='Stamen terrain')  # Or 'CartoDB positron'\n",
    "\n",
    "# Selected NEON Sites\n",
    "for idx, feature in neon_sites_tn_allprods_gdf.iterrows():\n",
    "    folium.Marker(location=[feature.geometry.y, feature.geometry.x], \n",
    "                  icon=folium.Icon(color='green'),\n",
    "                  popup=\"<b>NEON</b> {0} - {1} ({2})\".format(\n",
    "                      feature['siteCode'], feature['siteName'], feature['domainName'])\n",
    "                 ).add_to(m)\n",
    "\n",
    "# Highlight the sites that have the desired stream data\n",
    "for idx, feature in neon_sites_tn_gdf.iterrows():\n",
    "    folium.CircleMarker(location=[feature.geometry.y, feature.geometry.x], \n",
    "                        radius=10, color='red', fill=False,\n",
    "                        popup=\"<b>NEON SELECTED.</b> {0} - {1} ({2})\".format(\n",
    "                            feature['siteCode'], feature['siteName'], feature['domainName'])\n",
    "                       ).add_to(m)\n",
    "\n",
    "# Set the map extent (bounds) to the extent of the selected NEON sites\n",
    "m.fit_bounds(m.get_bounds())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<folium.map.Marker at 0x7f8b1397e5c0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# LTER sites\n",
    "for idx, row in lter_sites_df.iterrows():\n",
    "    folium.Marker(location=[row.latitude, row.longitude], \n",
    "                  icon=folium.Icon(color='gray'),\n",
    "                  popup=\"<b>LTER</b> site {}\".format(row['site_name'])\n",
    "                 ).add_to(m)\n",
    "\n",
    "# Single GLEON site\n",
    "folium.Marker(location=[36.733533, -88.11666], \n",
    "          icon=folium.Icon(color='blue'),\n",
    "          popup=\"<b>GLEON</b> Kentucky Lake site\"\n",
    "         ).add_to(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><iframe src=\"data:text/html;charset=utf-8;base64,<!DOCTYPE html>
<head>    
    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
    <script>L_PREFER_CANVAS=false; L_NO_TOUCH=false; L_DISABLE_3D=false;</script>
    <script src="https://cdn.jsdelivr.net/npm/leaflet@1.4.0/dist/leaflet.js"></script>
    <script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
    <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.4.0/dist/leaflet.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css"/>
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
    <link rel="stylesheet" href="https://rawcdn.githack.com/python-visualization/folium/master/folium/templates/leaflet.awesome.rotate.css"/>
    <style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
    <style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
    
    <meta name="viewport" content="width=device-width,
        initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
    <style>#map_1430db2b7b744e0babb7e577ca197170 {
        position: relative;
        width: 100.0%;
        height: 100.0%;
        left: 0.0%;
        top: 0.0%;
        }
    </style>
</head>
<body>    
    
    <div class="folium-map" id="map_1430db2b7b744e0babb7e577ca197170" ></div>
</body>
<script>    
    
    
        var bounds = null;
    

    var map_1430db2b7b744e0babb7e577ca197170 = L.map(
        'map_1430db2b7b744e0babb7e577ca197170', {
        center: [0, 0],
        zoom: 1,
        maxBounds: bounds,
        layers: [],
        worldCopyJump: false,
        crs: L.CRS.EPSG3857,
        zoomControl: true,
        });


    
    var tile_layer_62e1ca2457bb4eacb228c7aaf115f5c0 = L.tileLayer(
        'https://stamen-tiles-{s}.a.ssl.fastly.net/terrain/{z}/{x}/{y}.jpg',
        {
        "attribution": null,
        "detectRetina": false,
        "maxNativeZoom": 18,
        "maxZoom": 18,
        "minZoom": 0,
        "noWrap": false,
        "opacity": 1,
        "subdomains": "abc",
        "tms": false
}).addTo(map_1430db2b7b744e0babb7e577ca197170);
    
        var marker_5670f9c829d94f4c8b77cb1164cf24c1 = L.marker(
            [32.541529, -87.798151],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_18f8e43fc33d49dea4cbd16af1eb07ac = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_5670f9c829d94f4c8b77cb1164cf24c1.setIcon(icon_18f8e43fc33d49dea4cbd16af1eb07ac);
            
    
            var popup_2322876c3e05482a8ae65b3c328765ae = L.popup({maxWidth: '100%'
            
            });

            
                var html_0ce9ef6f904842dca06592e565913287 = $(`<div id="html_0ce9ef6f904842dca06592e565913287" style="width: 100.0%; height: 100.0%;"><b>NEON</b> BLWA - Black Warrior River Site, RELOCATABLE (Ozarks Complex)</div>`)[0];
                popup_2322876c3e05482a8ae65b3c328765ae.setContent(html_0ce9ef6f904842dca06592e565913287);
            

            marker_5670f9c829d94f4c8b77cb1164cf24c1.bindPopup(popup_2322876c3e05482a8ae65b3c328765ae)
            ;

            
        
    
        var marker_0b95e3f52f85442ab26ba39de8ac8b01 = L.marker(
            [32.541727, -87.803877],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_218245aebc8d47b7bd37886c5810baa4 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_0b95e3f52f85442ab26ba39de8ac8b01.setIcon(icon_218245aebc8d47b7bd37886c5810baa4);
            
    
            var popup_d2845f96226c4913a44e1eb5a945b65d = L.popup({maxWidth: '100%'
            
            });

            
                var html_1c7de22748a14bfbaed8b6758f9b95ed = $(`<div id="html_1c7de22748a14bfbaed8b6758f9b95ed" style="width: 100.0%; height: 100.0%;"><b>NEON</b> DELA - Dead Lake Site, RELOCATABLE (Ozarks Complex)</div>`)[0];
                popup_d2845f96226c4913a44e1eb5a945b65d.setContent(html_1c7de22748a14bfbaed8b6758f9b95ed);
            

            marker_0b95e3f52f85442ab26ba39de8ac8b01.bindPopup(popup_d2845f96226c4913a44e1eb5a945b65d)
            ;

            
        
    
        var marker_c657a07a974f421c91cbcf724b369167 = L.marker(
            [35.68896, -83.50195],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_56cd7cf860314d0d803d3994d9be67e5 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_c657a07a974f421c91cbcf724b369167.setIcon(icon_56cd7cf860314d0d803d3994d9be67e5);
            
    
            var popup_36578748897f46e9879a164f5db60d1c = L.popup({maxWidth: '100%'
            
            });

            
                var html_59c1cde2a354458595d5a29004070ddf = $(`<div id="html_59c1cde2a354458595d5a29004070ddf" style="width: 100.0%; height: 100.0%;"><b>NEON</b> GRSM - Great Smoky Mountains National Park Site, RELOCATABLE (Appalachians and Cumberland Plateau)</div>`)[0];
                popup_36578748897f46e9879a164f5db60d1c.setContent(html_59c1cde2a354458595d5a29004070ddf);
            

            marker_c657a07a974f421c91cbcf724b369167.bindPopup(popup_36578748897f46e9879a164f5db60d1c)
            ;

            
        
    
        var marker_285035dbfc8e4d468992711d895aa633 = L.marker(
            [35.690428, -83.50379],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_4512cf0ed98b45f9aad4d12a046d2e39 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_285035dbfc8e4d468992711d895aa633.setIcon(icon_4512cf0ed98b45f9aad4d12a046d2e39);
            
    
            var popup_d64744a2c0554847b86862aad281cdd5 = L.popup({maxWidth: '100%'
            
            });

            
                var html_01f4efc2d8db47b68ef7121f8399751b = $(`<div id="html_01f4efc2d8db47b68ef7121f8399751b" style="width: 100.0%; height: 100.0%;"><b>NEON</b> LECO - LeConte Creek Site, RELOCATABLE (Appalachians and Cumberland Plateau)</div>`)[0];
                popup_d64744a2c0554847b86862aad281cdd5.setContent(html_01f4efc2d8db47b68ef7121f8399751b);
            

            marker_285035dbfc8e4d468992711d895aa633.bindPopup(popup_d64744a2c0554847b86862aad281cdd5)
            ;

            
        
    
        var marker_bdb887801101488e80f3d47e98d90ac1 = L.marker(
            [31.853861, -88.161181],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_136413f6fc7e49cd982229ce9c7962e9 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_bdb887801101488e80f3d47e98d90ac1.setIcon(icon_136413f6fc7e49cd982229ce9c7962e9);
            
    
            var popup_f3b6167ca68047c0b1072e4dbfcfdff0 = L.popup({maxWidth: '100%'
            
            });

            
                var html_a88e7499fa534a0caffb17675a9023d4 = $(`<div id="html_a88e7499fa534a0caffb17675a9023d4" style="width: 100.0%; height: 100.0%;"><b>NEON</b> LENO - Lenoir Landing Site, RELOCATABLE (Ozarks Complex)</div>`)[0];
                popup_f3b6167ca68047c0b1072e4dbfcfdff0.setContent(html_a88e7499fa534a0caffb17675a9023d4);
            

            marker_bdb887801101488e80f3d47e98d90ac1.bindPopup(popup_f3b6167ca68047c0b1072e4dbfcfdff0)
            ;

            
        
    
        var marker_8028c5a06a694374aadf1812933ee26c = L.marker(
            [32.960365, -87.407688],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_b55a9ceb5add467d8fe02700bb8debb8 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_8028c5a06a694374aadf1812933ee26c.setIcon(icon_b55a9ceb5add467d8fe02700bb8debb8);
            
    
            var popup_11e36f76d4b54f3990944ed6e299337a = L.popup({maxWidth: '100%'
            
            });

            
                var html_079caeb1415446e8a9be1bd096d831f1 = $(`<div id="html_079caeb1415446e8a9be1bd096d831f1" style="width: 100.0%; height: 100.0%;"><b>NEON</b> MAYF - Mayfield Creek Site, CORE (Ozarks Complex)</div>`)[0];
                popup_11e36f76d4b54f3990944ed6e299337a.setContent(html_079caeb1415446e8a9be1bd096d831f1);
            

            marker_8028c5a06a694374aadf1812933ee26c.bindPopup(popup_11e36f76d4b54f3990944ed6e299337a)
            ;

            
        
    
        var marker_3427d28b0f0a4adc9bc30f47a1f46a2c = L.marker(
            [37.378314, -80.524847],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_d16d1b47e058409392c02c9b3cde979a = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_3427d28b0f0a4adc9bc30f47a1f46a2c.setIcon(icon_d16d1b47e058409392c02c9b3cde979a);
            
    
            var popup_864bfa896ab7474c830a9ca045903588 = L.popup({maxWidth: '100%'
            
            });

            
                var html_86f19b934a22498a8ef234b7225cba87 = $(`<div id="html_86f19b934a22498a8ef234b7225cba87" style="width: 100.0%; height: 100.0%;"><b>NEON</b> MLBS - Mountain Lake Biological Station Site, RELOCATABLE (Appalachians and Cumberland Plateau)</div>`)[0];
                popup_864bfa896ab7474c830a9ca045903588.setContent(html_86f19b934a22498a8ef234b7225cba87);
            

            marker_3427d28b0f0a4adc9bc30f47a1f46a2c.bindPopup(popup_864bfa896ab7474c830a9ca045903588)
            ;

            
        
    
        var marker_126827fa1f264f13a95c28a6843ef233 = L.marker(
            [35.964128, -84.282588],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_18aa8da991e54002a51bf27398cbe02c = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_126827fa1f264f13a95c28a6843ef233.setIcon(icon_18aa8da991e54002a51bf27398cbe02c);
            
    
            var popup_63be2dc170344a2ca1ea894c68c2c0b7 = L.popup({maxWidth: '100%'
            
            });

            
                var html_f83d9302fd004e52afedf3d50916d469 = $(`<div id="html_f83d9302fd004e52afedf3d50916d469" style="width: 100.0%; height: 100.0%;"><b>NEON</b> ORNL - Oak Ridge Site, CORE (Appalachians and Cumberland Plateau)</div>`)[0];
                popup_63be2dc170344a2ca1ea894c68c2c0b7.setContent(html_f83d9302fd004e52afedf3d50916d469);
            

            marker_126827fa1f264f13a95c28a6843ef233.bindPopup(popup_63be2dc170344a2ca1ea894c68c2c0b7)
            ;

            
        
    
        var marker_b0f9857b05da4452b790afe40d198608 = L.marker(
            [32.95047, -87.393259],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_0619a1fe33cb45709a201c1ee0474b97 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_b0f9857b05da4452b790afe40d198608.setIcon(icon_0619a1fe33cb45709a201c1ee0474b97);
            
    
            var popup_82f3c838b95c42e68f572ddecf9af76a = L.popup({maxWidth: '100%'
            
            });

            
                var html_feffb7872555495a9f846bfef6698319 = $(`<div id="html_feffb7872555495a9f846bfef6698319" style="width: 100.0%; height: 100.0%;"><b>NEON</b> TALL - Talladega National Forest Site, CORE (Ozarks Complex)</div>`)[0];
                popup_82f3c838b95c42e68f572ddecf9af76a.setContent(html_feffb7872555495a9f846bfef6698319);
            

            marker_b0f9857b05da4452b790afe40d198608.bindPopup(popup_82f3c838b95c42e68f572ddecf9af76a)
            ;

            
        
    
        var marker_3bee115d7598405b8e52e7c3fc2ef487 = L.marker(
            [31.853431, -88.158872],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_4f4d0adec8434307a28289ef51d3c320 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_3bee115d7598405b8e52e7c3fc2ef487.setIcon(icon_4f4d0adec8434307a28289ef51d3c320);
            
    
            var popup_407d7868107c405fb4e2db4744b1d0eb = L.popup({maxWidth: '100%'
            
            });

            
                var html_ee1d9760f72d4628be0d89d030acbf89 = $(`<div id="html_ee1d9760f72d4628be0d89d030acbf89" style="width: 100.0%; height: 100.0%;"><b>NEON</b> TOMB - Tombigbee River Site, RELOCATABLE (Ozarks Complex)</div>`)[0];
                popup_407d7868107c405fb4e2db4744b1d0eb.setContent(html_ee1d9760f72d4628be0d89d030acbf89);
            

            marker_3bee115d7598405b8e52e7c3fc2ef487.bindPopup(popup_407d7868107c405fb4e2db4744b1d0eb)
            ;

            
        
    
        var marker_0b4b07057379410a8d8eac88f62ebd02 = L.marker(
            [35.957378, -84.279251],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_ed63875f7d7149bbbfc1f925b8b67d2f = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_0b4b07057379410a8d8eac88f62ebd02.setIcon(icon_ed63875f7d7149bbbfc1f925b8b67d2f);
            
    
            var popup_3f01a15b942741d186d9748638245b40 = L.popup({maxWidth: '100%'
            
            });

            
                var html_e3fa8586cbd54b0e91fd1dd62fd90fe3 = $(`<div id="html_e3fa8586cbd54b0e91fd1dd62fd90fe3" style="width: 100.0%; height: 100.0%;"><b>NEON</b> WALK - Walker Branch Site, CORE (Appalachians and Cumberland Plateau)</div>`)[0];
                popup_3f01a15b942741d186d9748638245b40.setContent(html_e3fa8586cbd54b0e91fd1dd62fd90fe3);
            

            marker_0b4b07057379410a8d8eac88f62ebd02.bindPopup(popup_3f01a15b942741d186d9748638245b40)
            ;

            
        
    
            var circle_marker_9ba85501a65a495898fca8fbab82032f = L.circleMarker(
                [32.541529, -87.798151],
                {
  "bubblingMouseEvents": true,
  "color": "red",
  "dashArray": null,
  "dashOffset": null,
  "fill": false,
  "fillColor": "red",
  "fillOpacity": 0.2,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 10,
  "stroke": true,
  "weight": 3
}
                )
                .addTo(map_1430db2b7b744e0babb7e577ca197170);
            
    
            var popup_de2dde6a37f543b48216b1d8f1d09f39 = L.popup({maxWidth: '100%'
            
            });

            
                var html_a69791b119b345aaa2570ad2750080c9 = $(`<div id="html_a69791b119b345aaa2570ad2750080c9" style="width: 100.0%; height: 100.0%;"><b>NEON SELECTED.</b> BLWA - Black Warrior River Site, RELOCATABLE (Ozarks Complex)</div>`)[0];
                popup_de2dde6a37f543b48216b1d8f1d09f39.setContent(html_a69791b119b345aaa2570ad2750080c9);
            

            circle_marker_9ba85501a65a495898fca8fbab82032f.bindPopup(popup_de2dde6a37f543b48216b1d8f1d09f39)
            ;

            
        
    
            var circle_marker_ca2d2c443caf4ec8883e58f957211ff0 = L.circleMarker(
                [35.690428, -83.50379],
                {
  "bubblingMouseEvents": true,
  "color": "red",
  "dashArray": null,
  "dashOffset": null,
  "fill": false,
  "fillColor": "red",
  "fillOpacity": 0.2,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 10,
  "stroke": true,
  "weight": 3
}
                )
                .addTo(map_1430db2b7b744e0babb7e577ca197170);
            
    
            var popup_70c82c0231bb48ba8302eaf2d5d93732 = L.popup({maxWidth: '100%'
            
            });

            
                var html_931aef38b9124496aa1054f99ad1cb38 = $(`<div id="html_931aef38b9124496aa1054f99ad1cb38" style="width: 100.0%; height: 100.0%;"><b>NEON SELECTED.</b> LECO - LeConte Creek Site, RELOCATABLE (Appalachians and Cumberland Plateau)</div>`)[0];
                popup_70c82c0231bb48ba8302eaf2d5d93732.setContent(html_931aef38b9124496aa1054f99ad1cb38);
            

            circle_marker_ca2d2c443caf4ec8883e58f957211ff0.bindPopup(popup_70c82c0231bb48ba8302eaf2d5d93732)
            ;

            
        
    
            var circle_marker_cf0dcdf816ef4d9790cb8a65e06a52f8 = L.circleMarker(
                [32.960365, -87.407688],
                {
  "bubblingMouseEvents": true,
  "color": "red",
  "dashArray": null,
  "dashOffset": null,
  "fill": false,
  "fillColor": "red",
  "fillOpacity": 0.2,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 10,
  "stroke": true,
  "weight": 3
}
                )
                .addTo(map_1430db2b7b744e0babb7e577ca197170);
            
    
            var popup_9de72c832fe64b9293eb74c00aac5d19 = L.popup({maxWidth: '100%'
            
            });

            
                var html_c6e3c46a0fbd4967a78aa7918754fa88 = $(`<div id="html_c6e3c46a0fbd4967a78aa7918754fa88" style="width: 100.0%; height: 100.0%;"><b>NEON SELECTED.</b> MAYF - Mayfield Creek Site, CORE (Ozarks Complex)</div>`)[0];
                popup_9de72c832fe64b9293eb74c00aac5d19.setContent(html_c6e3c46a0fbd4967a78aa7918754fa88);
            

            circle_marker_cf0dcdf816ef4d9790cb8a65e06a52f8.bindPopup(popup_9de72c832fe64b9293eb74c00aac5d19)
            ;

            
        
    
            var circle_marker_2bf3dae7345f475a9892b5e5aaca96bf = L.circleMarker(
                [31.853431, -88.158872],
                {
  "bubblingMouseEvents": true,
  "color": "red",
  "dashArray": null,
  "dashOffset": null,
  "fill": false,
  "fillColor": "red",
  "fillOpacity": 0.2,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 10,
  "stroke": true,
  "weight": 3
}
                )
                .addTo(map_1430db2b7b744e0babb7e577ca197170);
            
    
            var popup_fc0e43261f7d445abe614c52b2948717 = L.popup({maxWidth: '100%'
            
            });

            
                var html_4ba17487137445ab910a83261dec909f = $(`<div id="html_4ba17487137445ab910a83261dec909f" style="width: 100.0%; height: 100.0%;"><b>NEON SELECTED.</b> TOMB - Tombigbee River Site, RELOCATABLE (Ozarks Complex)</div>`)[0];
                popup_fc0e43261f7d445abe614c52b2948717.setContent(html_4ba17487137445ab910a83261dec909f);
            

            circle_marker_2bf3dae7345f475a9892b5e5aaca96bf.bindPopup(popup_fc0e43261f7d445abe614c52b2948717)
            ;

            
        
    
            var circle_marker_2978d02ae73d4526bfda831d6d59d602 = L.circleMarker(
                [35.957378, -84.279251],
                {
  "bubblingMouseEvents": true,
  "color": "red",
  "dashArray": null,
  "dashOffset": null,
  "fill": false,
  "fillColor": "red",
  "fillOpacity": 0.2,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 10,
  "stroke": true,
  "weight": 3
}
                )
                .addTo(map_1430db2b7b744e0babb7e577ca197170);
            
    
            var popup_3b851874a02f45e2bdb13894fe534b4b = L.popup({maxWidth: '100%'
            
            });

            
                var html_9118fa8422ba4f899fded9429ad86441 = $(`<div id="html_9118fa8422ba4f899fded9429ad86441" style="width: 100.0%; height: 100.0%;"><b>NEON SELECTED.</b> WALK - Walker Branch Site, CORE (Appalachians and Cumberland Plateau)</div>`)[0];
                popup_3b851874a02f45e2bdb13894fe534b4b.setContent(html_9118fa8422ba4f899fded9429ad86441);
            

            circle_marker_2978d02ae73d4526bfda831d6d59d602.bindPopup(popup_3b851874a02f45e2bdb13894fe534b4b)
            ;

            
        
    
                

                map_1430db2b7b744e0babb7e577ca197170.fitBounds(
                    [[31.853431, -88.161181], [37.378314, -80.524847]],
                    {}
                    );
            
    
        var marker_0d7b2b6a64fb43b981a006ea579816f8 = L.marker(
            [44.211999999999996, -122.256],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_51cba3e0b06e4cd5963cc9ac565063d7 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_0d7b2b6a64fb43b981a006ea579816f8.setIcon(icon_51cba3e0b06e4cd5963cc9ac565063d7);
            
    
            var popup_11c8d5eac4934ca390e6ffd496870fe5 = L.popup({maxWidth: '100%'
            
            });

            
                var html_3bdfe5d319f94235b84d2c155ab4cff3 = $(`<div id="html_3bdfe5d319f94235b84d2c155ab4cff3" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Andrews Forest LTER</div>`)[0];
                popup_11c8d5eac4934ca390e6ffd496870fe5.setContent(html_3bdfe5d319f94235b84d2c155ab4cff3);
            

            marker_0d7b2b6a64fb43b981a006ea579816f8.bindPopup(popup_11c8d5eac4934ca390e6ffd496870fe5)
            ;

            
        
    
        var marker_31a3d7a7932a4e499ccf09e0254934e5 = L.marker(
            [68.62826, -149.59598],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_4557d65b120e490a840c78e8bf6bb4fd = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_31a3d7a7932a4e499ccf09e0254934e5.setIcon(icon_4557d65b120e490a840c78e8bf6bb4fd);
            
    
            var popup_1da544b93aa34f1fac8dbc845a650258 = L.popup({maxWidth: '100%'
            
            });

            
                var html_053a8aa322e14a65b3aa792ef30a4fdc = $(`<div id="html_053a8aa322e14a65b3aa792ef30a4fdc" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Arctic LTER</div>`)[0];
                popup_1da544b93aa34f1fac8dbc845a650258.setContent(html_053a8aa322e14a65b3aa792ef30a4fdc);
            

            marker_31a3d7a7932a4e499ccf09e0254934e5.bindPopup(popup_1da544b93aa34f1fac8dbc845a650258)
            ;

            
        
    
        var marker_8b55613b5ec841b7ad0bc4353069f433 = L.marker(
            [39.1, -76.3],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_9410911d6af64ec9b6e3c28dd6461188 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_8b55613b5ec841b7ad0bc4353069f433.setIcon(icon_9410911d6af64ec9b6e3c28dd6461188);
            
    
            var popup_59ae91a7dd77484c9a69a5b34be7edb1 = L.popup({maxWidth: '100%'
            
            });

            
                var html_e9e90c9ff45c4da3960154a36ca1cb50 = $(`<div id="html_e9e90c9ff45c4da3960154a36ca1cb50" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Baltimore Ecosystem Study</div>`)[0];
                popup_59ae91a7dd77484c9a69a5b34be7edb1.setContent(html_e9e90c9ff45c4da3960154a36ca1cb50);
            

            marker_8b55613b5ec841b7ad0bc4353069f433.bindPopup(popup_59ae91a7dd77484c9a69a5b34be7edb1)
            ;

            
        
    
        var marker_6e846b0f88624cab8fe93dbd415da1e8 = L.marker(
            [64.85848, -147.84668],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_da41205ddb9740a5ac21c58e7d6d4d1f = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_6e846b0f88624cab8fe93dbd415da1e8.setIcon(icon_da41205ddb9740a5ac21c58e7d6d4d1f);
            
    
            var popup_2ea206a7148a4f558f16429002080713 = L.popup({maxWidth: '100%'
            
            });

            
                var html_318e053cb8ca44b0b97668a8d8f08233 = $(`<div id="html_318e053cb8ca44b0b97668a8d8f08233" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Bonanza Creek LTER</div>`)[0];
                popup_2ea206a7148a4f558f16429002080713.setContent(html_318e053cb8ca44b0b97668a8d8f08233);
            

            marker_6e846b0f88624cab8fe93dbd415da1e8.bindPopup(popup_2ea206a7148a4f558f16429002080713)
            ;

            
        
    
        var marker_64089882dd9245e7bb88cf9678f13f7d = L.marker(
            [33.427, -111.93299999999999],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_7b7eff83fe55440d9d9f509b32f5621d = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_64089882dd9245e7bb88cf9678f13f7d.setIcon(icon_7b7eff83fe55440d9d9f509b32f5621d);
            
    
            var popup_79fba57d9e6c44ec9d976808a421b228 = L.popup({maxWidth: '100%'
            
            });

            
                var html_7b617b2367a34a8eb63e863d244e0212 = $(`<div id="html_7b617b2367a34a8eb63e863d244e0212" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Central Arizona - Phoenix LTER</div>`)[0];
                popup_79fba57d9e6c44ec9d976808a421b228.setContent(html_7b617b2367a34a8eb63e863d244e0212);
            

            marker_64089882dd9245e7bb88cf9678f13f7d.bindPopup(popup_79fba57d9e6c44ec9d976808a421b228)
            ;

            
        
    
        var marker_1107a0d8788d45b4b6ea3dae574d36d5 = L.marker(
            [45.401, -93.20100000000001],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_f3ce345d9a61451b91ea7f87e5cf2728 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_1107a0d8788d45b4b6ea3dae574d36d5.setIcon(icon_f3ce345d9a61451b91ea7f87e5cf2728);
            
    
            var popup_6c3045fd4d594ec2a27e92d6ea840803 = L.popup({maxWidth: '100%'
            
            });

            
                var html_9068bf81193e4fdcaf52972f2479a2ba = $(`<div id="html_9068bf81193e4fdcaf52972f2479a2ba" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Cedar Creek LTER</div>`)[0];
                popup_6c3045fd4d594ec2a27e92d6ea840803.setContent(html_9068bf81193e4fdcaf52972f2479a2ba);
            

            marker_1107a0d8788d45b4b6ea3dae574d36d5.bindPopup(popup_6c3045fd4d594ec2a27e92d6ea840803)
            ;

            
        
    
        var marker_0e139e4190834ee38b33feda071a4348 = L.marker(
            [35.0, -83.5],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_f1873d91e0e34c7fb37cfd46f5b0f324 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_0e139e4190834ee38b33feda071a4348.setIcon(icon_f1873d91e0e34c7fb37cfd46f5b0f324);
            
    
            var popup_43fecf29db124ddb9cad00c17646d177 = L.popup({maxWidth: '100%'
            
            });

            
                var html_1fbf280f064e4f68b5f0c3942aa1aaf6 = $(`<div id="html_1fbf280f064e4f68b5f0c3942aa1aaf6" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Coweeta LTER</div>`)[0];
                popup_43fecf29db124ddb9cad00c17646d177.setContent(html_1fbf280f064e4f68b5f0c3942aa1aaf6);
            

            marker_0e139e4190834ee38b33feda071a4348.bindPopup(popup_43fecf29db124ddb9cad00c17646d177)
            ;

            
        
    
        var marker_2218c1a0812c41afa1475453e7a7ef3a = L.marker(
            [25.46821, -80.85328],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_a1c5720d090a47b788d2d3ce0b97ac3c = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_2218c1a0812c41afa1475453e7a7ef3a.setIcon(icon_a1c5720d090a47b788d2d3ce0b97ac3c);
            
    
            var popup_ade97160d14741d394eb46da30199b34 = L.popup({maxWidth: '100%'
            
            });

            
                var html_6c0ecfd78006450e87f6f2c7ece645dd = $(`<div id="html_6c0ecfd78006450e87f6f2c7ece645dd" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Florida Coastal Everglades LTER</div>`)[0];
                popup_ade97160d14741d394eb46da30199b34.setContent(html_6c0ecfd78006450e87f6f2c7ece645dd);
            

            marker_2218c1a0812c41afa1475453e7a7ef3a.bindPopup(popup_ade97160d14741d394eb46da30199b34)
            ;

            
        
    
        var marker_c0e0e10c86df47c3a86c1d86972ff213 = L.marker(
            [31.427, -81.37100000000001],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_6405cc55b13540c9b97cb6a66d5ea249 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_c0e0e10c86df47c3a86c1d86972ff213.setIcon(icon_6405cc55b13540c9b97cb6a66d5ea249);
            
    
            var popup_5cc77dcb746244d58a4304294976136f = L.popup({maxWidth: '100%'
            
            });

            
                var html_5fadb6d886ab462c9e8cb8a1d7772660 = $(`<div id="html_5fadb6d886ab462c9e8cb8a1d7772660" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Georgia Coastal Ecosystems LTER</div>`)[0];
                popup_5cc77dcb746244d58a4304294976136f.setContent(html_5fadb6d886ab462c9e8cb8a1d7772660);
            

            marker_c0e0e10c86df47c3a86c1d86972ff213.bindPopup(popup_5cc77dcb746244d58a4304294976136f)
            ;

            
        
    
        var marker_39ecf75753ef4daea00c7ed463491ee5 = L.marker(
            [43.94, -71.751],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_07f6142ff039449895fe3bfbbc934b47 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_39ecf75753ef4daea00c7ed463491ee5.setIcon(icon_07f6142ff039449895fe3bfbbc934b47);
            
    
            var popup_b047cba046cf453785fb9e06d84e95cd = L.popup({maxWidth: '100%'
            
            });

            
                var html_0f0e2ac08a4042bdbee19edda039379d = $(`<div id="html_0f0e2ac08a4042bdbee19edda039379d" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Hubbard Brook LTER</div>`)[0];
                popup_b047cba046cf453785fb9e06d84e95cd.setContent(html_0f0e2ac08a4042bdbee19edda039379d);
            

            marker_39ecf75753ef4daea00c7ed463491ee5.bindPopup(popup_b047cba046cf453785fb9e06d84e95cd)
            ;

            
        
    
        var marker_05ea57ce39834c0da0a57840bcf857b0 = L.marker(
            [42.53, -72.19],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_3d92d85790fd4e3b83dbb011995d8fa0 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_05ea57ce39834c0da0a57840bcf857b0.setIcon(icon_3d92d85790fd4e3b83dbb011995d8fa0);
            
    
            var popup_5e2d138ab1a642c1942740761dd93a70 = L.popup({maxWidth: '100%'
            
            });

            
                var html_05aa6d36379e4eea85b0106e0ed444ac = $(`<div id="html_05aa6d36379e4eea85b0106e0ed444ac" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Harvard Forest LTER</div>`)[0];
                popup_5e2d138ab1a642c1942740761dd93a70.setContent(html_05aa6d36379e4eea85b0106e0ed444ac);
            

            marker_05ea57ce39834c0da0a57840bcf857b0.bindPopup(popup_5e2d138ab1a642c1942740761dd93a70)
            ;

            
        
    
        var marker_f6ab808bf6c04f73b76384d9d9316741 = L.marker(
            [32.61785, -106.73985],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_8cdfad0069f94cafad8105ac6f061c2f = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_f6ab808bf6c04f73b76384d9d9316741.setIcon(icon_8cdfad0069f94cafad8105ac6f061c2f);
            
    
            var popup_84ae2b8788b54c6d96690eea4b7ca3af = L.popup({maxWidth: '100%'
            
            });

            
                var html_9926b7840d874375a3de33b153c87193 = $(`<div id="html_9926b7840d874375a3de33b153c87193" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Jornada Basin LTER</div>`)[0];
                popup_84ae2b8788b54c6d96690eea4b7ca3af.setContent(html_9926b7840d874375a3de33b153c87193);
            

            marker_f6ab808bf6c04f73b76384d9d9316741.bindPopup(popup_84ae2b8788b54c6d96690eea4b7ca3af)
            ;

            
        
    
        var marker_ed966500add24f0ca0552f4a70aa76c3 = L.marker(
            [42.4, -85.4],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_0e272519259e46c3897d1af17f8a9d7a = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_ed966500add24f0ca0552f4a70aa76c3.setIcon(icon_0e272519259e46c3897d1af17f8a9d7a);
            
    
            var popup_1dbd464552af4a87bf0db6fcb5196e15 = L.popup({maxWidth: '100%'
            
            });

            
                var html_7eb9cd9dc77b4c54a182254e2bdae006 = $(`<div id="html_7eb9cd9dc77b4c54a182254e2bdae006" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Kellogg Biological Station LTER</div>`)[0];
                popup_1dbd464552af4a87bf0db6fcb5196e15.setContent(html_7eb9cd9dc77b4c54a182254e2bdae006);
            

            marker_ed966500add24f0ca0552f4a70aa76c3.bindPopup(popup_1dbd464552af4a87bf0db6fcb5196e15)
            ;

            
        
    
        var marker_198645b4b326455bb1a24e274196c821 = L.marker(
            [39.093, -96.575],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_936d9aebbb4f4552b6537c4c63f05566 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_198645b4b326455bb1a24e274196c821.setIcon(icon_936d9aebbb4f4552b6537c4c63f05566);
            
    
            var popup_46085434afe04050b6ccc12ed262892f = L.popup({maxWidth: '100%'
            
            });

            
                var html_60a9a0af8ae84e21a039f83c71c9d965 = $(`<div id="html_60a9a0af8ae84e21a039f83c71c9d965" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Konza Prairie LTER</div>`)[0];
                popup_46085434afe04050b6ccc12ed262892f.setContent(html_60a9a0af8ae84e21a039f83c71c9d965);
            

            marker_198645b4b326455bb1a24e274196c821.bindPopup(popup_46085434afe04050b6ccc12ed262892f)
            ;

            
        
    
        var marker_456abe78664c44b48a5c9eb743d6736d = L.marker(
            [18.3, -65.8],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_022460e7b15c482c9e703e68c0233dd6 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_456abe78664c44b48a5c9eb743d6736d.setIcon(icon_022460e7b15c482c9e703e68c0233dd6);
            
    
            var popup_5c2678c8299d4142953d324e6ec29b1e = L.popup({maxWidth: '100%'
            
            });

            
                var html_bfa311fdc0d2403e9cb0b705c316a411 = $(`<div id="html_bfa311fdc0d2403e9cb0b705c316a411" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Luquillo LTER</div>`)[0];
                popup_5c2678c8299d4142953d324e6ec29b1e.setContent(html_bfa311fdc0d2403e9cb0b705c316a411);
            

            marker_456abe78664c44b48a5c9eb743d6736d.bindPopup(popup_5c2678c8299d4142953d324e6ec29b1e)
            ;

            
        
    
        var marker_f04ce86f3fc64c938000723460bb3a81 = L.marker(
            [-77.0, 163.783],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_ef23df4594794b2dbc28655e6df8d568 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_f04ce86f3fc64c938000723460bb3a81.setIcon(icon_ef23df4594794b2dbc28655e6df8d568);
            
    
            var popup_1aaece85050c42f989512915a16b1ea7 = L.popup({maxWidth: '100%'
            
            });

            
                var html_1ef072ca78b143b1b6c52c491e191563 = $(`<div id="html_1ef072ca78b143b1b6c52c491e191563" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site McMurdo Dry Valleys LTER</div>`)[0];
                popup_1aaece85050c42f989512915a16b1ea7.setContent(html_1ef072ca78b143b1b6c52c491e191563);
            

            marker_f04ce86f3fc64c938000723460bb3a81.bindPopup(popup_1aaece85050c42f989512915a16b1ea7)
            ;

            
        
    
        var marker_1f2ba8d81d494ac5af526c74645071a7 = L.marker(
            [35.084, -106.62],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_182ca1ebb67849c4a5f38684f0919433 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_1f2ba8d81d494ac5af526c74645071a7.setIcon(icon_182ca1ebb67849c4a5f38684f0919433);
            
    
            var popup_8658506274ad41838413a93ce5318d88 = L.popup({maxWidth: '100%'
            
            });

            
                var html_ac417027fb5141fb90854809e8f5023f = $(`<div id="html_ac417027fb5141fb90854809e8f5023f" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site  The LTER Network Office</div>`)[0];
                popup_8658506274ad41838413a93ce5318d88.setContent(html_ac417027fb5141fb90854809e8f5023f);
            

            marker_1f2ba8d81d494ac5af526c74645071a7.bindPopup(popup_8658506274ad41838413a93ce5318d88)
            ;

            
        
    
        var marker_7d95a0d3fa3b4e8587dfd3829c3e2a0e = L.marker(
            [46.0124, -89.67200000000001],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_ef230e57cef44988b32d8e8b97c70013 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_7d95a0d3fa3b4e8587dfd3829c3e2a0e.setIcon(icon_ef230e57cef44988b32d8e8b97c70013);
            
    
            var popup_da0b611618724e31acf076bbbd85608e = L.popup({maxWidth: '100%'
            
            });

            
                var html_2a2ccbbf06a741e794a0797d88ded309 = $(`<div id="html_2a2ccbbf06a741e794a0797d88ded309" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site North Temperate Lakes LTER</div>`)[0];
                popup_da0b611618724e31acf076bbbd85608e.setContent(html_2a2ccbbf06a741e794a0797d88ded309);
            

            marker_7d95a0d3fa3b4e8587dfd3829c3e2a0e.bindPopup(popup_da0b611618724e31acf076bbbd85608e)
            ;

            
        
    
        var marker_796837e7e89f42e9a79a149df752937d = L.marker(
            [39.993, -105.375],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_15488e22168d4f4aa27a96d89d2616c1 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_796837e7e89f42e9a79a149df752937d.setIcon(icon_15488e22168d4f4aa27a96d89d2616c1);
            
    
            var popup_cc11fcbda1de400fbf5a1dfa0f84b91d = L.popup({maxWidth: '100%'
            
            });

            
                var html_9bb78679b3104017b526719d40b36535 = $(`<div id="html_9bb78679b3104017b526719d40b36535" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Niwot Ridge LTER</div>`)[0];
                popup_cc11fcbda1de400fbf5a1dfa0f84b91d.setContent(html_9bb78679b3104017b526719d40b36535);
            

            marker_796837e7e89f42e9a79a149df752937d.bindPopup(popup_cc11fcbda1de400fbf5a1dfa0f84b91d)
            ;

            
        
    
        var marker_a8ae8d5e8a144a7c96e5e8f2ec2a6fbe = L.marker(
            [-64.77417, -64.0545],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_95e040e20cdb47ad9b6b857e4f47ac8d = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_a8ae8d5e8a144a7c96e5e8f2ec2a6fbe.setIcon(icon_95e040e20cdb47ad9b6b857e4f47ac8d);
            
    
            var popup_b35d1571046b4f8f871e37be7edc0d27 = L.popup({maxWidth: '100%'
            
            });

            
                var html_0876545388c24493971c4bae616cac22 = $(`<div id="html_0876545388c24493971c4bae616cac22" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Palmer Antarctica LTER</div>`)[0];
                popup_b35d1571046b4f8f871e37be7edc0d27.setContent(html_0876545388c24493971c4bae616cac22);
            

            marker_a8ae8d5e8a144a7c96e5e8f2ec2a6fbe.bindPopup(popup_b35d1571046b4f8f871e37be7edc0d27)
            ;

            
        
    
        var marker_2c8fa183a0164f14af2dacb13649e834 = L.marker(
            [42.75899999999999, -70.891],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_b4d95e5fb6c34f53b7c5af948f7c23a4 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_2c8fa183a0164f14af2dacb13649e834.setIcon(icon_b4d95e5fb6c34f53b7c5af948f7c23a4);
            
    
            var popup_4e5aaf3f4c8a45c88ccf090498a0c5cb = L.popup({maxWidth: '100%'
            
            });

            
                var html_a541686ef94b4753b98df6383bdb8669 = $(`<div id="html_a541686ef94b4753b98df6383bdb8669" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Plum Island Ecosystems LTER</div>`)[0];
                popup_4e5aaf3f4c8a45c88ccf090498a0c5cb.setContent(html_a541686ef94b4753b98df6383bdb8669);
            

            marker_2c8fa183a0164f14af2dacb13649e834.bindPopup(popup_4e5aaf3f4c8a45c88ccf090498a0c5cb)
            ;

            
        
    
        var marker_cc20b954ab42422fb72d0fd80adb91b1 = L.marker(
            [34.4125, -119.8422],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_7b4544f50c4a44baa3ab6234fb739417 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_cc20b954ab42422fb72d0fd80adb91b1.setIcon(icon_7b4544f50c4a44baa3ab6234fb739417);
            
    
            var popup_90f33148fa2a4e0c85c732cb896f04c0 = L.popup({maxWidth: '100%'
            
            });

            
                var html_9a38197837a640d9bd6129d72791ee0b = $(`<div id="html_9a38197837a640d9bd6129d72791ee0b" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Santa Barbara Coastal LTER</div>`)[0];
                popup_90f33148fa2a4e0c85c732cb896f04c0.setContent(html_9a38197837a640d9bd6129d72791ee0b);
            

            marker_cc20b954ab42422fb72d0fd80adb91b1.bindPopup(popup_90f33148fa2a4e0c85c732cb896f04c0)
            ;

            
        
    
        var marker_679ae6e098fc46029bfc50cc266ec865 = L.marker(
            [34.353, -106.882],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_6051a4baa0154439945eb9241329ac0a = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_679ae6e098fc46029bfc50cc266ec865.setIcon(icon_6051a4baa0154439945eb9241329ac0a);
            
    
            var popup_a7bd1cecbf5748b5a0419c46b622eb78 = L.popup({maxWidth: '100%'
            
            });

            
                var html_5841c7e482904edb87f15dc563780318 = $(`<div id="html_5841c7e482904edb87f15dc563780318" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Sevilleta LTER</div>`)[0];
                popup_a7bd1cecbf5748b5a0419c46b622eb78.setContent(html_5841c7e482904edb87f15dc563780318);
            

            marker_679ae6e098fc46029bfc50cc266ec865.bindPopup(popup_a7bd1cecbf5748b5a0419c46b622eb78)
            ;

            
        
    
        var marker_eda15b334470489b8f7acafdba156079 = L.marker(
            [40.827, -104.72399999999999],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_7fddcb1617dd48d3920ad194d5af88ed = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_eda15b334470489b8f7acafdba156079.setIcon(icon_7fddcb1617dd48d3920ad194d5af88ed);
            
    
            var popup_4f7aa3b78cdd47b1be495abf5b8bb79a = L.popup({maxWidth: '100%'
            
            });

            
                var html_34f4e6820c9245afbc2d4a11ba746d68 = $(`<div id="html_34f4e6820c9245afbc2d4a11ba746d68" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Shortgrass Steppe</div>`)[0];
                popup_4f7aa3b78cdd47b1be495abf5b8bb79a.setContent(html_34f4e6820c9245afbc2d4a11ba746d68);
            

            marker_eda15b334470489b8f7acafdba156079.bindPopup(popup_4f7aa3b78cdd47b1be495abf5b8bb79a)
            ;

            
        
    
        var marker_10a07c7bb46545b8af22dd7b433e43c2 = L.marker(
            [37.283, -75.913],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_607abf63d9894554a853082b8da0f5e2 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_10a07c7bb46545b8af22dd7b433e43c2.setIcon(icon_607abf63d9894554a853082b8da0f5e2);
            
    
            var popup_e399c8534b1544a3b087e7bc61e443f1 = L.popup({maxWidth: '100%'
            
            });

            
                var html_c7f7e91e2d62467e9eabc41fd12d570c = $(`<div id="html_c7f7e91e2d62467e9eabc41fd12d570c" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Virginia Coast Reserve LTER</div>`)[0];
                popup_e399c8534b1544a3b087e7bc61e443f1.setContent(html_c7f7e91e2d62467e9eabc41fd12d570c);
            

            marker_10a07c7bb46545b8af22dd7b433e43c2.bindPopup(popup_e399c8534b1544a3b087e7bc61e443f1)
            ;

            
        
    
        var marker_981cc3fc36b54db096da34f14433a269 = L.marker(
            [32.8736, -120.2798],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_02dc15939c7e4d10aeeb57d82fee8cce = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_981cc3fc36b54db096da34f14433a269.setIcon(icon_02dc15939c7e4d10aeeb57d82fee8cce);
            
    
            var popup_3cf865436b064451a9d1e4d53f6f54c5 = L.popup({maxWidth: '100%'
            
            });

            
                var html_bf5e603a1ebb4beaa75b4456db7b2f20 = $(`<div id="html_bf5e603a1ebb4beaa75b4456db7b2f20" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site California Current Ecosystem LTER</div>`)[0];
                popup_3cf865436b064451a9d1e4d53f6f54c5.setContent(html_bf5e603a1ebb4beaa75b4456db7b2f20);
            

            marker_981cc3fc36b54db096da34f14433a269.bindPopup(popup_3cf865436b064451a9d1e4d53f6f54c5)
            ;

            
        
    
        var marker_0a0c4079330e4be69e6e52d85f3883dc = L.marker(
            [-17.49085, -149.82612],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_6098c94fe5f840c993b01f759ec33534 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'gray',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_0a0c4079330e4be69e6e52d85f3883dc.setIcon(icon_6098c94fe5f840c993b01f759ec33534);
            
    
            var popup_2176e950de4343e8966dee2c685cee12 = L.popup({maxWidth: '100%'
            
            });

            
                var html_c7c895444d6c447b93499085a6dc60d4 = $(`<div id="html_c7c895444d6c447b93499085a6dc60d4" style="width: 100.0%; height: 100.0%;"><b>LTER</b> site Moorea Coral Reef LTER</div>`)[0];
                popup_2176e950de4343e8966dee2c685cee12.setContent(html_c7c895444d6c447b93499085a6dc60d4);
            

            marker_0a0c4079330e4be69e6e52d85f3883dc.bindPopup(popup_2176e950de4343e8966dee2c685cee12)
            ;

            
        
    
        var marker_22177f6685354264af3185d98b4a5432 = L.marker(
            [36.733533, -88.11666],
            {
                icon: new L.Icon.Default(),
                }
            ).addTo(map_1430db2b7b744e0babb7e577ca197170);
        
    

                var icon_262ea368e3084ebdb252ecd154904ab4 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'blue',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_22177f6685354264af3185d98b4a5432.setIcon(icon_262ea368e3084ebdb252ecd154904ab4);
            
    
            var popup_fdbaf91274f447678eb81cff1c73a5da = L.popup({maxWidth: '100%'
            
            });

            
                var html_89c58210baf2485d9e2fa2b8f0ec7865 = $(`<div id="html_89c58210baf2485d9e2fa2b8f0ec7865" style="width: 100.0%; height: 100.0%;"><b>GLEON</b> Kentucky Lake site</div>`)[0];
                popup_fdbaf91274f447678eb81cff1c73a5da.setContent(html_89c58210baf2485d9e2fa2b8f0ec7865);
            

            marker_22177f6685354264af3185d98b4a5432.bindPopup(popup_fdbaf91274f447678eb81cff1c73a5da)
            ;

            
        
</script>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f8b1397ef60>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now render the map\n",
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "toc-hr-collapsed": false
   },
   "source": [
    "# EXTRA CREDIT: Read in time series data for a NEON site"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**This is pretty involved, so I won't go into it. You can look at it on your own if you're interested in NEON data or in probing further at an interaction with a REST API.**\n",
    "\n",
    "Extract and list all the \"Data Products\" for one of the 3 selected NEON stream sites.\n",
    "Borrowed heavily from https://nbviewer.jupyter.org/gist/jzollerneon/3d0519e1f26db80b755cc865ef218d58"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Select the site, data product and time period"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "SITECODE = 'LECO'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "neon_leco_site_gdf = neon_sites_tn_gdf.loc[neon_sites_tn_gdf['siteCode'] == SITECODE]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('DP1.00001.001', '2D wind speed and direction'),\n",
       " ('DP1.00002.001', 'Single aspirated air temperature'),\n",
       " ('DP1.00004.001', 'Barometric pressure'),\n",
       " ('DP1.00023.001', 'Shortwave and longwave radiation (net radiometer)'),\n",
       " ('DP1.00024.001', 'Photosynthetically active radiation (PAR)'),\n",
       " ('DP1.00098.001', 'Relative humidity'),\n",
       " ('DP1.20002.001', 'Land-water interface images'),\n",
       " ('DP1.20016.001', 'Elevation of surface water'),\n",
       " ('DP1.20033.001', 'Nitrate in surface water'),\n",
       " ('DP1.20042.001', 'Photosynthetically active radiation at water surface'),\n",
       " ('DP1.20048.001', 'Stream discharge field collection'),\n",
       " ('DP1.20053.001', 'Temperature (PRT) in surface water'),\n",
       " ('DP1.20066.001', 'Aquatic plant bryophyte macroalgae clip harvest'),\n",
       " ('DP1.20072.001',\n",
       "  'Aquatic plant, bryophyte, lichen, and macroalgae point counts in wadeable streams'),\n",
       " ('DP1.20093.001', 'Chemical properties of surface water'),\n",
       " ('DP1.20097.001', 'Dissolved gases in surface water'),\n",
       " ('DP1.20105.001', 'Fish sequences DNA barcode'),\n",
       " ('DP1.20107.001',\n",
       "  'Fish electrofishing, gill netting, and fyke netting counts'),\n",
       " ('DP1.20120.001', 'Macroinvertebrate collection'),\n",
       " ('DP1.20126.001', 'Macroinvertebrate DNA barcode'),\n",
       " ('DP1.20138.001', 'Surface water microbe cell count'),\n",
       " ('DP1.20163.001',\n",
       "  'Periphyton, seston, and phytoplankton chemical properties'),\n",
       " ('DP1.20166.001', 'Periphyton, seston, and phytoplankton collection'),\n",
       " ('DP1.20190.001', 'Reaeration field and lab collection'),\n",
       " ('DP1.20191.001', 'Riparian vegetation % cover'),\n",
       " ('DP1.20193.001', 'Salt-based stream discharge'),\n",
       " ('DP1.20194.001', 'Sediment chemical properties'),\n",
       " ('DP1.20197.001', 'Sediment physical properties'),\n",
       " ('DP1.20206.001', 'Stable isotope concentrations in surface waters'),\n",
       " ('DP1.20267.001', 'Gauge height'),\n",
       " ('DP1.20275.001', 'Riparian composition and structure'),\n",
       " ('DP1.20277.001', 'Benthic microbe group abundances'),\n",
       " ('DP1.20278.001', 'Surface water microbe group abundances'),\n",
       " ('DP1.20279.001', 'Benthic microbe metagenome sequences'),\n",
       " ('DP1.20280.001', 'Benthic microbe marker gene sequences'),\n",
       " ('DP1.20281.001', 'Surface water microbe metagenome sequences'),\n",
       " ('DP1.20282.001', 'Surface water microbe marker gene sequences'),\n",
       " ('DP1.20288.001', 'Water quality'),\n",
       " ('DP4.00131.001', 'Stream morphology map')]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neon_leco_site_dataproducts = neon_leco_site_gdf.iloc[0]['dataProducts']\n",
    "sorted([(dp['dataProductCode'], dp['dataProductTitle']) \n",
    "        for dp in neon_leco_site_dataproducts])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('DP1.20288.001',\n",
       " ['2017-05',\n",
       "  '2018-01',\n",
       "  '2018-02',\n",
       "  '2018-03',\n",
       "  '2018-04',\n",
       "  '2018-05',\n",
       "  '2018-06',\n",
       "  '2018-07',\n",
       "  '2018-08',\n",
       "  '2018-09',\n",
       "  '2018-10',\n",
       "  '2018-11',\n",
       "  '2018-12',\n",
       "  '2019-01',\n",
       "  '2019-02',\n",
       "  '2019-03',\n",
       "  '2019-04',\n",
       "  '2019-05',\n",
       "  '2019-06',\n",
       "  '2019-07',\n",
       "  '2019-08',\n",
       "  '2019-09',\n",
       "  '2019-10',\n",
       "  '2019-11',\n",
       "  '2019-12',\n",
       "  '2020-01'])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BASEPRODUCTCODE = 'DP1.20288'\n",
    "for data_product in neon_leco_site_dataproducts:\n",
    "    if BASEPRODUCTCODE in data_product['dataProductCode']:\n",
    "        dataProductCode = data_product['dataProductCode']\n",
    "        availableMonths = data_product['availableMonths']\n",
    "\n",
    "dataProductCode, availableMonths"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Issue the \"data\" REST API request and examine the response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_response = requests.get(\"{}{}/{}/{}/{}\".format(neon_api_baseurl, 'data', dataProductCode, SITECODE, availableMonths[-1]))\n",
    "data_response_json = data_response.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://data.neonscience.org/api/v0/data/DP1.20288.001/LECO/2020-01'"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_response.url"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['data'])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_response_json.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(dict, 4)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(data_response_json['data']), len(data_response_json['data'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['files', 'productCode', 'siteCode', 'month'])"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_response_json['data'].keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(list,\n",
       " [{'crc32': '5329791e6205b2dd765ed9cd355b17cd',\n",
       "   'name': 'NEON.D07.LECO.DP1.20288.001.102.100.100.waq_instantaneous.2020-01.basic.20200207T013737Z.csv',\n",
       "   'size': '4777536',\n",
       "   'url': 'https://neon-prod-pub-1.s3.data.neonscience.org/NEON.DOM.SITE.DP1.20288.001/PROV/LECO/20200101T000000--20200201T000000/basic/NEON.D07.LECO.DP1.20288.001.102.100.100.waq_instantaneous.2020-01.basic.20200207T013737Z.csv?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20200226T205015Z&X-Amz-SignedHeaders=host&X-Amz-Expires=3599&X-Amz-Credential=pub-internal-read%2F20200226%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Signature=edd2f42abc563820f962ef395bcdff01fd3b9786195beb353233042b805878a7'},\n",
       "  {'crc32': 'e28d3f717ad1fc2ded6a13e54e51c180',\n",
       "   'name': 'NEON.D07.LECO.DP1.20288.001.sensor_positions.20200207T013737Z.csv',\n",
       "   'size': '456',\n",
       "   'url': 'https://neon-prod-pub-1.s3.data.neonscience.org/NEON.DOM.SITE.DP1.20288.001/PROV/LECO/20200101T000000--20200201T000000/basic/NEON.D07.LECO.DP1.20288.001.sensor_positions.20200207T013737Z.csv?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20200226T205015Z&X-Amz-SignedHeaders=host&X-Amz-Expires=3600&X-Amz-Credential=pub-internal-read%2F20200226%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Signature=82554f8c64de03b34662adbe45c2ecd9e94db2ca02a7b1d9da8b2bee3dfd0c5b'}])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(data_response_json['data']['files']), data_response_json['data']['files'][0:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "toc-hr-collapsed": false
   },
   "source": [
    "## Read, parse and plot the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "datafile_url = data_response_json['data']['files'][0]['url']\n",
    "csv_data_response = requests.get(datafile_url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://neon-prod-pub-1.s3.data.neonscience.org/NEON.DOM.SITE.DP1.20288.001/PROV/LECO/20200101T000000--20200201T000000/basic/NEON.D07.LECO.DP1.20288.001.102.100.100.waq_instantaneous.2020-01.basic.20200207T013737Z.csv?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20200226T205015Z&X-Amz-SignedHeaders=host&X-Amz-Expires=3599&X-Amz-Credential=pub-internal-read%2F20200226%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Signature=edd2f42abc563820f962ef395bcdff01fd3b9786195beb353233042b805878a7'"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datafile_url"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Since the data is in memory and not a file, we need to convert it before loading it into a pandas DataFrame\n",
    "df = pd.read_csv(StringIO(csv_data_response.text))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 44735 entries, 0 to 44734\n",
      "Data columns (total 28 columns):\n",
      "startDateTime                   44735 non-null object\n",
      "endDateTime                     44735 non-null object\n",
      "sensorDepth                     0 non-null float64\n",
      "sensorDepthExpUncert            0 non-null float64\n",
      "sensorDepthFinalQF              0 non-null float64\n",
      "specificConductance             19285 non-null float64\n",
      "specificConductanceExpUncert    19285 non-null float64\n",
      "specificCondFinalQF             44735 non-null int64\n",
      "dissolvedOxygen                 19288 non-null float64\n",
      "dissolvedOxygenExpUncert        19288 non-null float64\n",
      "dissolvedOxygenFinalQF          44735 non-null int64\n",
      "dissolvedOxygenSaturation       19288 non-null float64\n",
      "dissolvedOxygenSatExpUncert     19288 non-null float64\n",
      "dissolvedOxygenSatFinalQF       44735 non-null int64\n",
      "pH                              19288 non-null float64\n",
      "pHExpUncert                     19288 non-null float64\n",
      "pHFinalQF                       44735 non-null int64\n",
      "chlorophyll                     19288 non-null float64\n",
      "chlorophyllExpUncert            19288 non-null float64\n",
      "chlorophyllFinalQF              44735 non-null int64\n",
      "turbidity                       19288 non-null float64\n",
      "turbidityExpUncert              19288 non-null float64\n",
      "turbidityFinalQF                44735 non-null int64\n",
      "fDOM                            19275 non-null float64\n",
      "rawCalibratedfDOM               19275 non-null float64\n",
      "fDOMExpUncert                   19275 non-null float64\n",
      "fDOMFinalQF                     44735 non-null int64\n",
      "buoyNAFlag                      0 non-null float64\n",
      "dtypes: float64(19), int64(7), object(2)\n",
      "memory usage: 9.6+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "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>startDateTime</th>\n",
       "      <th>endDateTime</th>\n",
       "      <th>sensorDepth</th>\n",
       "      <th>sensorDepthExpUncert</th>\n",
       "      <th>sensorDepthFinalQF</th>\n",
       "      <th>specificConductance</th>\n",
       "      <th>specificConductanceExpUncert</th>\n",
       "      <th>specificCondFinalQF</th>\n",
       "      <th>dissolvedOxygen</th>\n",
       "      <th>dissolvedOxygenExpUncert</th>\n",
       "      <th>...</th>\n",
       "      <th>chlorophyllExpUncert</th>\n",
       "      <th>chlorophyllFinalQF</th>\n",
       "      <th>turbidity</th>\n",
       "      <th>turbidityExpUncert</th>\n",
       "      <th>turbidityFinalQF</th>\n",
       "      <th>fDOM</th>\n",
       "      <th>rawCalibratedfDOM</th>\n",
       "      <th>fDOMExpUncert</th>\n",
       "      <th>fDOMFinalQF</th>\n",
       "      <th>buoyNAFlag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-01T00:00:30Z</td>\n",
       "      <td>2020-01-01T00:00:30Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.71</td>\n",
       "      <td>0.2</td>\n",
       "      <td>1</td>\n",
       "      <td>12.21</td>\n",
       "      <td>0.24</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.86</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0</td>\n",
       "      <td>1.51</td>\n",
       "      <td>1.32</td>\n",
       "      <td>0.43</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-01T00:01:30Z</td>\n",
       "      <td>2020-01-01T00:01:30Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.71</td>\n",
       "      <td>0.2</td>\n",
       "      <td>1</td>\n",
       "      <td>12.21</td>\n",
       "      <td>0.24</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.79</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0</td>\n",
       "      <td>1.52</td>\n",
       "      <td>1.33</td>\n",
       "      <td>0.43</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          startDateTime           endDateTime  sensorDepth  \\\n",
       "0  2020-01-01T00:00:30Z  2020-01-01T00:00:30Z          NaN   \n",
       "1  2020-01-01T00:01:30Z  2020-01-01T00:01:30Z          NaN   \n",
       "\n",
       "   sensorDepthExpUncert  sensorDepthFinalQF  specificConductance  \\\n",
       "0                   NaN                 NaN                16.71   \n",
       "1                   NaN                 NaN                16.71   \n",
       "\n",
       "   specificConductanceExpUncert  specificCondFinalQF  dissolvedOxygen  \\\n",
       "0                           0.2                    1            12.21   \n",
       "1                           0.2                    1            12.21   \n",
       "\n",
       "   dissolvedOxygenExpUncert  ...  chlorophyllExpUncert  chlorophyllFinalQF  \\\n",
       "0                      0.24  ...                   0.0                   1   \n",
       "1                      0.24  ...                   0.0                   1   \n",
       "\n",
       "   turbidity  turbidityExpUncert  turbidityFinalQF  fDOM  rawCalibratedfDOM  \\\n",
       "0       1.86                0.03                 0  1.51               1.32   \n",
       "1       1.79                0.03                 0  1.52               1.33   \n",
       "\n",
       "   fDOMExpUncert  fDOMFinalQF  buoyNAFlag  \n",
       "0           0.43            1         NaN  \n",
       "1           0.43            1         NaN  \n",
       "\n",
       "[2 rows x 28 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "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>startDateTime</th>\n",
       "      <th>endDateTime</th>\n",
       "      <th>sensorDepth</th>\n",
       "      <th>sensorDepthExpUncert</th>\n",
       "      <th>sensorDepthFinalQF</th>\n",
       "      <th>specificConductance</th>\n",
       "      <th>specificConductanceExpUncert</th>\n",
       "      <th>specificCondFinalQF</th>\n",
       "      <th>dissolvedOxygen</th>\n",
       "      <th>dissolvedOxygenExpUncert</th>\n",
       "      <th>...</th>\n",
       "      <th>chlorophyllExpUncert</th>\n",
       "      <th>chlorophyllFinalQF</th>\n",
       "      <th>turbidity</th>\n",
       "      <th>turbidityExpUncert</th>\n",
       "      <th>turbidityFinalQF</th>\n",
       "      <th>fDOM</th>\n",
       "      <th>rawCalibratedfDOM</th>\n",
       "      <th>fDOMExpUncert</th>\n",
       "      <th>fDOMFinalQF</th>\n",
       "      <th>buoyNAFlag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>44733</th>\n",
       "      <td>2020-01-31T23:58:00Z</td>\n",
       "      <td>2020-01-31T23:58:00Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44734</th>\n",
       "      <td>2020-01-31T23:59:00Z</td>\n",
       "      <td>2020-01-31T23:59:00Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              startDateTime           endDateTime  sensorDepth  \\\n",
       "44733  2020-01-31T23:58:00Z  2020-01-31T23:58:00Z          NaN   \n",
       "44734  2020-01-31T23:59:00Z  2020-01-31T23:59:00Z          NaN   \n",
       "\n",
       "       sensorDepthExpUncert  sensorDepthFinalQF  specificConductance  \\\n",
       "44733                   NaN                 NaN                  NaN   \n",
       "44734                   NaN                 NaN                  NaN   \n",
       "\n",
       "       specificConductanceExpUncert  specificCondFinalQF  dissolvedOxygen  \\\n",
       "44733                           NaN                    1              NaN   \n",
       "44734                           NaN                    1              NaN   \n",
       "\n",
       "       dissolvedOxygenExpUncert  ...  chlorophyllExpUncert  \\\n",
       "44733                       NaN  ...                   NaN   \n",
       "44734                       NaN  ...                   NaN   \n",
       "\n",
       "       chlorophyllFinalQF  turbidity  turbidityExpUncert  turbidityFinalQF  \\\n",
       "44733                   1        NaN                 NaN                 1   \n",
       "44734                   1        NaN                 NaN                 1   \n",
       "\n",
       "       fDOM  rawCalibratedfDOM  fDOMExpUncert  fDOMFinalQF  buoyNAFlag  \n",
       "44733   NaN                NaN            NaN            1         NaN  \n",
       "44734   NaN                NaN            NaN            1         NaN  \n",
       "\n",
       "[2 rows x 28 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('2020-01-01T00:00:30Z', str)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[0]['endDateTime'], type(df.iloc[0]['endDateTime']) # It's a string type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['end_dt'] = pd.to_datetime(df['endDateTime'])\n",
    "df.set_index('end_dt', drop=False, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.dissolvedOxygen.plot(title='dissolvedOxygen', figsize=(15, 4));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Scatter plots of pH and Chlorophyll vs Dissolved Oxygen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df.plot(kind='scatter', x='dissolvedOxygen', y='pH', color='Blue', label='pH',\n",
    "             figsize=(8, 6))\n",
    "df.plot(kind='scatter', x='dissolvedOxygen', y='chlorophyll', color='Green', label='chlorophyll',\n",
    "        ax=ax, ylim=[0,10]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:whwtimeseries]",
   "language": "python",
   "name": "conda-env-whwtimeseries-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  },
  "toc-autonumbering": true,
  "toc-showcode": false,
  "toc-showmarkdowntxt": false,
  "toc-showtags": false
 },
 "nbformat": 4,
 "nbformat_minor": 4
}