Notebook_Example.ipynb

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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src='https://i.ibb.co/vPkH8ht/EU-Copernicus-EUM-WEKEO-banner-logo.png' align='right' width='75%'/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Authors:**  <br>\n",
    "**Copyright:** 2022 AUTHORS NAMES <br>\n",
    "**License:** MIT"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-success\">\n",
    "<h3>NOTEBOOK TITLE</h3></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NOTEBOOK INTRODUCTION\n",
    "\n",
    "### Data used (example - you can change this to suit your data sets)\n",
    "\n",
    "| Product Description | Data Store collection ID| Product Navigator | WEkEO HDA ID | WEkEO metadata |\n",
    "|:--------------------:|:-----------------------:|:-------------:|:-----------------:|:-----------------:|\n",
    "| Sentinel-3 SLSTR level-1B | EO:EUM:DAT:0411 | <a href=\"https://navigator.eumetsat.int/product/EO:EUM:DAT:SENTINEL-3:SL_1_RBT___NTC?query=SLSTR&s=advanced\" target=\"_blank\">link</a> | EO:EUM:DAT:SENTINEL-3:SL_1_RBT___ | <a href=\"https://www.wekeo.eu/data?view=dataset&dataset=EO%3AEUM%3ADAT%3ASENTINEL-3%3ASL_1_RBT___&initial=1\" target=\"_blank\">link</a> |\n",
    "\n",
    "### Learning outcomes\n",
    "\n",
    "At the end of this notebook you will know;\n",
    "* How a certain type of data is collected by satellites.\n",
    "* How you can use a certain type of data for a specific environmental application.\n",
    "* How to visualise a certain type of data.\n",
    "* How to analyse a certain type of data with a certain type of method.\n",
    "\n",
    "\n",
    "### Outline\n",
    "\n",
    "Here you could describe your notebook, and perhaps include <a href=\"https://notebook.wekeo.eu/\" target=\"_blank\">links</a> to any relevant external content. \n",
    "\n",
    "<div class=\"alert alert-info\" role=\"alert\">\n",
    "\n",
    "## <a id='TOC_TOP'></a>Contents\n",
    "\n",
    "</div>\n",
    "    \n",
    " 1. [Section 1](#section1)\n",
    " 2. [Section 2](#section2)\n",
    " 3. [Section 3](#section3)\n",
    " 4. [Section 4](#section4)\n",
    "\n",
    "\n",
    "<hr>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# library imports (some common examples used and available on the WEkEO Jupyter Lab)\n",
    "import cartopy.crs as ccrs\n",
    "import glob\n",
    "import inspect\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as mticker\n",
    "import numpy as np\n",
    "import os\n",
    "import warnings\n",
    "import xarray as xr\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info\" role=\"alert\">\n",
    "\n",
    "## <a id='section1'></a>1. Section 1\n",
    "[Back to top](#TOC_TOP)\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's good to set the scene here - describe your data/application/method"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info\" role=\"alert\">\n",
    "\n",
    "## <a id='section2'></a>2. Section 2\n",
    "[Back to top](#TOC_TOP)\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here you could start by downloading the relevant data for your notebook\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info\" role=\"alert\">\n",
    "\n",
    "## <a id='section3'></a>3. Section 3\n",
    "[Back to top](#TOC_TOP)\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is where you can split your workflow in to different sections. It's good to try and keep these short - one section for one action. Each should be a mix of code cells and markdown cells that describe what the code does and why. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CODE SECTION"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Due to the bands we have selected, and the fact that this is a level-1 product, the image above is quite difficult to interpret. However with some understanding of the synoptic scale and typical patterns of different ocean and atmosphere features, we can see that the TIR bands can reveal variability associated with sea and land surfaces, and clouds/the atmosphere. This is the fundamental basis of how we can use this data for a diverse range of applications."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-danger\" role=\"alert\">\n",
    "\n",
    "## <a id='section4'></a>Section 4.\n",
    "[Back to top](#TOC_TOP)\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\">\n",
    "\n",
    "### Challenge:\n",
    "\n",
    "A final section of your notebook could invite the user to try and adapt your notebook for their own purposes. This is not necessary but can really help people to learn by applying their new knowled\n",
    " <div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "solution2": "hidden",
    "solution2_first": true
   },
   "outputs": [],
   "source": [
    "# Enter your solution here\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  }
 ],
 "metadata": {
  "author": "Ben Loveday, Hayley Evers-King",
  "description": "This Jupyter Notebook discusses the radiance and brightness temperature bands in SLSTR level-1B products.",
  "github": "https://github.com/wekeo/learn-slstr/blob/master/1_SLSTR_introductory/1_4_SLSTR_bands_imagery.ipynb",
  "image": "../img/thumbs/1_4_SLSTR_bands_imagery_thumb.png",
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   "language": "python",
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   "pygments_lexer": "ipython3",
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  "link": "https://jupyterhub-wekeo.apps.eumetsat.dpi.wekeo.eu/hub/user-redirect/lab/tree/public/ocean/learn-slstr/1_SLSTR_introductory/1_4_SLSTR_bands_imagery.ipynb",
  "tags": {
   "domain": "Ocean",
   "platform": "Sentinel-3",
   "sensor": "SLSTR",
   "tags": [
    "Top-of-atmosphere radiance",
    "Brightness temperature"
   ]
  },
  "title": "SLSTR bands and imagery"
 },
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