{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0",
   "metadata": {},
   "source": [
    "<a href=\"https://githubtocolab.com/gee-community/geemap/blob/master/examples/notebooks/nlcd_datapane.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\"/></a>\n",
    "\n",
    "Uncomment the following line to install [geemap](https://geemap.org) if needed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install geemap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2",
   "metadata": {},
   "source": [
    "To follow this tutorial, you need to [sign up](https://datapane.com/accounts/signup/) for an account with <https://datapane.com>, then install and authenticate the `datapane` Python package. More information can be found [here](https://docs.datapane.com/tutorials/tut-getting-started). \n",
    "\n",
    "- `pip install datapane`\n",
    "- `datapane login`\n",
    "- `datapane ping`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import ee\n",
    "import geemap.foliumap as geemap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4",
   "metadata": {},
   "outputs": [],
   "source": [
    "Map = geemap.Map(center=[40, -100], zoom=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Select the seven NLCD epoches after 2000.\n",
    "years = [\"2001\", \"2004\", \"2006\", \"2008\", \"2011\", \"2013\", \"2016\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get an NLCD image by year.\n",
    "def getNLCD(year):\n",
    "    # Import the NLCD collection.\n",
    "    dataset = ee.ImageCollection(\"USGS/NLCD_RELEASES/2016_REL\")\n",
    "\n",
    "    # Filter the collection by year.\n",
    "    nlcd = dataset.filter(ee.Filter.eq(\"system:index\", year)).first()\n",
    "\n",
    "    # Select the land cover band.\n",
    "    landcover = nlcd.select(\"landcover\")\n",
    "    return landcover"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7",
   "metadata": {},
   "outputs": [],
   "source": [
    "for year in years:\n",
    "    data = getNLCD(year)\n",
    "    Map.addLayer(data, {}, \"NLCD \" + year)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add the NLCD legend to the map.\n",
    "Map.add_legend(legend_title=\"NLCD Land Cover Classification\", builtin_legend=\"NLCD\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9",
   "metadata": {},
   "outputs": [],
   "source": [
    "Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "10",
   "metadata": {},
   "outputs": [],
   "source": [
    "Map.publish(name=\"National Land Cover Database (NLCD)\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}