{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "03e829e9",
   "metadata": {},
   "source": [
    "# GEDI_L4B Search and Visualize"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39343211",
   "metadata": {},
   "source": [
    "Authors: Nikita Susan (UAH), Aimee Barciauskas (Development Seed), Sumant Jha (MSFC/USRA), Alex Mandel (Development Seed)\n",
    "\n",
    "Date: April 7, 2023\n",
    "\n",
    "Description: In this example, we demonstrate how to access the GEDI L4B collection and granule data on the MAAP ADE, and then visualize the data using matplotlib."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "544e0985",
   "metadata": {},
   "source": [
    "## Run This Notebook\n",
    "To access and run this tutorial within MAAP's Algorithm Development Environment (ADE), please refer to the [\"Getting started with the MAAP\"](https://docs.maap-project.org/en/latest/getting_started/getting_started.html) section of our documentation.\n",
    "\n",
    "Disclaimer: it is highly recommended to run a tutorial within MAAP's ADE, which already includes packages specific to MAAP, such as maap-py. Running the tutorial outside of the MAAP ADE may lead to errors."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fa174dd",
   "metadata": {},
   "source": [
    "## About the Data\n",
    "\n",
    "GEDI L4B Gridded Aboveground Biomass Density, Version 2\n",
    "\n",
    "This dataset provides Global Ecosystem Dynamics Investigation (GEDI) Level 4 (L4) data, which has the purpose of providing mean aboveground biomass density (AGBD) and consists of the GEDI_L4A and GEDI_L4B collections. GEDI_L4B uses a sample present within each 1km cell to statistically infer mean AGBD. GEDI is attached to the International Space Station (ISS) and collects data globally between 51.6° N and 51.6° S latitudes at the highest resolution and densest sampling of any light detection and ranging (lidar) instrument in orbit to date; specifically, GEDI L4B data has a spatial resolution of 1km. (Source: [GEDI_L4B Version 2 User Guide](https://daac.ornl.gov/GEDI/guides/GEDI_L4B_Gridded_Biomass.html))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63a47555",
   "metadata": {},
   "source": [
    "## Additional Resources\n",
    "- [GEDI_L4B Version 2 Dataset Landing Page](https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2017) \n",
    "- [The GEDI Website](https://gedi.umd.edu/)\n",
    "- [Earthdata Search](https://search.earthdata.nasa.gov/search?q=GEDI_L4B&lat=49.70652984841501&long=-102.041015625&zoom=6)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e873e990",
   "metadata": {},
   "source": [
    "## Importing Packages"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ddd527f",
   "metadata": {},
   "source": [
    "Within your Jupyter Notebook, start by importing the **maap package**. Then invoke the **MAAP** constructor, setting the maap_host argument to **'api.maap-project.org'**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "751ea26d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from maap.maap import MAAP\n",
    "from matplotlib import pyplot\n",
    "import os\n",
    "import pprint\n",
    "import rasterio\n",
    "import boto3\n",
    "\n",
    "maap = MAAP(maap_host=\"api.maap-project.org\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8039c1fd",
   "metadata": {},
   "source": [
    "## Search for the Collection and Associated Granules\n",
    "\n",
    "Now, we will search for the collection using the collection short name:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "141ce670",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[{'concept-id': 'C2244602422-ORNL_CLOUD', 'revision-id': '7', 'format': 'application/echo10+xml', 'Collection': {'ShortName': 'GEDI_L4B_Gridded_Biomass_2017', 'VersionId': '2', 'InsertTime': '2022-03-29T00:00:00Z', 'LastUpdate': '2023-06-12T20:25:17Z', 'LongName': 'GEDI L4B Gridded Aboveground Biomass Density, Version 2', 'DataSetId': 'GEDI L4B Gridded Aboveground Biomass Density, Version 2', 'Description': \"This Global Ecosystem Dynamics Investigation (GEDI) L4B product provides 1 km x 1 km (1 km,  hereafter) estimates of mean aboveground biomass density (AGBD) based on observations from mission week 19 starting on 2019-04-18 to mission week 138 ending on 2021-08-04. The GEDI L4A Footprint Biomass product converts each high-quality waveform to an AGBD prediction, and the L4B product uses the sample present within the borders of each 1 km cell to statistically infer mean AGBD. The gridding procedure is described in the GEDI L4B Algorithm Theoretical Basis Document (ATBD). Patterson et al. (2019) describes the hybrid model-based mode of inference used in the L4B product. Corresponding 1 km estimates of the standard error of the mean are also provided in the L4B product. Uncertainty is due to both GEDI's sampling of the 1 km area (as opposed to making wall-to-wall observations) and the fact that L4A biomass values are modeled in a process subject to error instead of measured in a process that may be assumed to be error-free.\", 'DOI': {'DOI': '10.3334/ORNLDAAC/2017', 'Authority': 'https://doi.org'}, 'Orderable': 'false', 'Visible': 'true', 'RevisionDate': '2022-03-29T00:00:00Z', 'ProcessingLevelId': '4', 'ProcessingLevelDescription': 'model products', 'ArchiveCenter': 'ORNL_DAAC', 'CitationForExternalPublication': 'Dubayah, R.O., J. Armston, S.P. Healey, Z. Yang, P.L. Patterson, S. Saarela, G. Stahl, L. Duncanson, and J.R. Kellner. 2022. GEDI L4B Gridded Aboveground Biomass Density, Version 2. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2017', 'CollectionState': 'COMPLETE', 'MaintenanceAndUpdateFrequency': 'As needed', 'UseConstraints': {'LicenseURL': {'URL': 'https://science.nasa.gov/earth-science/earth-science-data/data-information-policy', 'Description': 'License URL for data use policy', 'Type': 'Data Use Policy', 'MimeType': 'text/html'}}, 'Price': '0', 'DataFormat': 'GeoTIFF', 'SpatialKeywords': {'Keyword': 'GLOBAL LAND'}, 'Temporal': {'RangeDateTime': {'BeginningDateTime': '2019-04-18T00:00:00Z', 'EndingDateTime': '2021-08-04T23:59:59Z'}}, 'Contacts': {'Contact': {'Role': 'ARCHIVER', 'OrganizationName': 'ORNL_DAAC', 'OrganizationAddresses': {'Address': {'StreetAddress': 'ORNL DAAC User Services Office, P.O. Box 2008, MS 6407, Oak Ridge National Laboratory', 'City': 'Oak Ridge', 'StateProvince': 'Tennessee', 'PostalCode': '37831-6407', 'Country': 'USA'}}, 'OrganizationPhones': {'Phone': {'Number': '(865) 241-3952', 'Type': 'Direct Line'}}, 'OrganizationEmails': {'Email': 'uso@daac.ornl.gov'}}}, 'ScienceKeywords': {'ScienceKeyword': [{'CategoryKeyword': 'EARTH SCIENCE', 'TopicKeyword': 'BIOSPHERE', 'TermKeyword': 'ECOSYSTEMS', 'VariableLevel1Keyword': {'Value': 'TERRESTRIAL ECOSYSTEMS'}}, {'CategoryKeyword': 'EARTH SCIENCE', 'TopicKeyword': 'BIOSPHERE', 'TermKeyword': 'VEGETATION', 'VariableLevel1Keyword': {'Value': 'BIOMASS'}}, {'CategoryKeyword': 'EARTH SCIENCE', 'TopicKeyword': 'SPECTRAL/ENGINEERING', 'TermKeyword': 'LIDAR', 'VariableLevel1Keyword': {'Value': 'LIDAR WAVEFORM'}}]}, 'Platforms': {'Platform': {'ShortName': 'ISS', 'LongName': 'MUSES', 'Type': 'Space Stations/Crewed Spacecraft', 'Instruments': {'Instrument': {'ShortName': 'GEDI', 'LongName': 'Global Ecosystem Dynamics Investigation'}}}}, 'Campaigns': {'Campaign': {'ShortName': 'GEDI', 'LongName': 'Global Ecosystem Dynamics Investigation'}}, 'OnlineAccessURLs': {'OnlineAccessURL': {'URL': 'https://daac.ornl.gov/gedi/GEDI_L4B_Gridded_Biomass/', 'URLDescription': 'This link allows direct data access via Earthdata login'}}, 'OnlineResources': {'OnlineResource': [{'URL': 'https://daac.ornl.gov/GEDI/guides/GEDI_L4B_Gridded_Biomass.html', 'Description': 'ORNL DAAC Data Set Documentation', 'Type': \"USER'S GUIDE\"}, {'URL': 'https://doi.org/10.3334/ORNLDAAC/2017', 'Description': 'Data set Landing Page DOI URL', 'Type': 'DATA SET LANDING PAGE'}, {'URL': 'https://data.ornldaac.earthdata.nasa.gov/public/gedi/GEDI_L4B_Gridded_Biomass/comp/GEDI_L4B_ATBD_v1.0.pdf', 'Description': 'GEDI L4B Gridded Aboveground Biomass Density, Version 2: GEDI_L4B_ATBD_v1.0.pdf', 'Type': 'GENERAL DOCUMENTATION'}, {'URL': 'https://data.ornldaac.earthdata.nasa.gov/public/gedi/GEDI_L4B_Gridded_Biomass/comp/GEDI_L4B_Gridded_Biomass.pdf', 'Description': 'GEDI L4B Gridded Aboveground Biomass Density, Version 2: GEDI_L4B_Gridded_Biomass.pdf', 'Type': 'GENERAL DOCUMENTATION'}, {'URL': 'https://daac.ornl.gov/GEDI/guides/GEDI_L4B_Gridded_Biomass_Fig1.png', 'Description': 'Gridded mean aboveground biomass density (top) and standard error of the mean (bottom).', 'Type': 'GET RELATED VISUALIZATION', 'MimeType': 'image/png'}, {'URL': 'https://gedi.umd.edu', 'Description': 'GEDI Project Site', 'Type': 'PROJECT HOME PAGE', 'MimeType': 'text/html'}, {'URL': 'https://webmap.ornl.gov/wcsdown/dataset.jsp?ds_id=2017', 'Description': 'Web Coverage Service for this collection.', 'Type': 'WEB COVERAGE SERVICE (WCS)', 'MimeType': 'application/gml+xml'}]}, 'Spatial': {'SpatialCoverageType': 'HORIZONTAL', 'HorizontalSpatialDomain': {'Geometry': {'CoordinateSystem': 'CARTESIAN', 'BoundingRectangle': {'WestBoundingCoordinate': '-180.00', 'NorthBoundingCoordinate': '52.00', 'EastBoundingCoordinate': '180.00', 'SouthBoundingCoordinate': '-52.00'}}}, 'GranuleSpatialRepresentation': 'CARTESIAN'}, 'DirectDistributionInformation': {'Region': 'us-west-2', 'S3BucketAndObjectPrefixName': 's3://ornl-cumulus-prod-protected/gedi/GEDI_L4B_Gridded_Biomass/', 'S3CredentialsAPIEndpoint': 'https://data.ornldaac.earthdata.nasa.gov/s3credentials', 'S3CredentialsAPIDocumentationURL': 'https://data.ornldaac.earthdata.nasa.gov/s3credentialsREADME'}}}]\n"
     ]
    }
   ],
   "source": [
    "collection = maap.searchCollection(cmr_host='cmr.earthdata.nasa.gov', short_name=\"GEDI_L4B_Gridded_Biomass_2017\", limit=100)\n",
    "print(collection)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56f227a3",
   "metadata": {},
   "source": [
    "Next, we can search for granules using the searchGranule function and the concept ID from our collection search above:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "aa586fe9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Got 10 results\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'GranuleUR': 'GEDI_L4B_Gridded_Biomass.GEDI04_B_MW019MW138_02_002_05_R01000M_PS.tif',\n",
       " 'InsertTime': '2022-03-29T00:00:00Z',\n",
       " 'LastUpdate': '2023-04-10T21:58:24Z',\n",
       " 'Collection': {'ShortName': 'GEDI_L4B_Gridded_Biomass_2017',\n",
       "  'VersionId': '2'},\n",
       " 'DataGranule': {'DataGranuleSizeInBytes': '20103343',\n",
       "  'SizeMBDataGranule': '20.103343',\n",
       "  'Checksum': {'Value': '025a141348906d5e612262218c496a2d468446ca30875439be6651d851bfbe23',\n",
       "   'Algorithm': 'SHA-256'},\n",
       "  'DayNightFlag': 'BOTH',\n",
       "  'ProductionDateTime': '2022-03-29T00:00:00Z'},\n",
       " 'Temporal': {'RangeDateTime': {'BeginningDateTime': '2019-04-18T00:00:00Z',\n",
       "   'EndingDateTime': '2021-08-04T23:59:59Z'}},\n",
       " 'Spatial': {'HorizontalSpatialDomain': {'Geometry': {'BoundingRectangle': {'WestBoundingCoordinate': '-180',\n",
       "     'NorthBoundingCoordinate': '52',\n",
       "     'EastBoundingCoordinate': '180',\n",
       "     'SouthBoundingCoordinate': '-52'}}}},\n",
       " 'MeasuredParameters': {'MeasuredParameter': [{'ParameterName': 'LIDAR WAVEFORM'},\n",
       "   {'ParameterName': 'BIOMASS'},\n",
       "   {'ParameterName': 'TERRESTRIAL ECOSYSTEMS'}]},\n",
       " 'Platforms': {'Platform': {'ShortName': 'ISS',\n",
       "   'Instruments': {'Instrument': {'ShortName': 'GEDI'}}}},\n",
       " 'Campaigns': {'Campaign': {'ShortName': 'GEDI'}},\n",
       " 'Price': '0',\n",
       " 'OnlineAccessURLs': {'OnlineAccessURL': [{'URL': 'https://data.ornldaac.earthdata.nasa.gov/protected/gedi/GEDI_L4B_Gridded_Biomass/data/GEDI04_B_MW019MW138_02_002_05_R01000M_PS.tif',\n",
       "    'URLDescription': 'Download GEDI04_B_MW019MW138_02_002_05_R01000M_PS.tif',\n",
       "    'MimeType': 'image/tiff'},\n",
       "   {'URL': 'https://data.ornldaac.earthdata.nasa.gov/public/gedi/GEDI_L4B_Gridded_Biomass/data/GEDI04_B_MW019MW138_02_002_05_R01000M_PS.tif.sha256',\n",
       "    'URLDescription': 'Download GEDI04_B_MW019MW138_02_002_05_R01000M_PS.tif.sha256'},\n",
       "   {'URL': 's3://ornl-cumulus-prod-protected/gedi/GEDI_L4B_Gridded_Biomass/data/GEDI04_B_MW019MW138_02_002_05_R01000M_PS.tif',\n",
       "    'URLDescription': 'This link provides direct download access via S3 to the granule',\n",
       "    'MimeType': 'image/tiff'}]},\n",
       " 'OnlineResources': {'OnlineResource': [{'URL': 'https://daac.ornl.gov/GEDI/guides/GEDI_L4B_Gridded_Biomass.html',\n",
       "    'Description': 'ORNL DAAC Data Set Documentation',\n",
       "    'Type': \"USER'S GUIDE\"},\n",
       "   {'URL': 'https://doi.org/10.3334/ORNLDAAC/2017',\n",
       "    'Description': 'Data set Landing Page DOI URL',\n",
       "    'Type': 'DATA SET LANDING PAGE'},\n",
       "   {'URL': 'https://daac.ornl.gov/daacdata/gedi/GEDI_L4B_Gridded_Biomass/comp/GEDI_L4B_ATBD_v1.0.pdf',\n",
       "    'Description': 'Data Set Documentation',\n",
       "    'Type': 'GENERAL DOCUMENTATION'},\n",
       "   {'URL': 'https://daac.ornl.gov/daacdata/gedi/GEDI_L4B_Gridded_Biomass/comp/GEDI_L4B_Gridded_Biomass.pdf',\n",
       "    'Description': 'Data Set Documentation',\n",
       "    'Type': 'GENERAL DOCUMENTATION'},\n",
       "   {'URL': 'https://webmap.ornl.gov/sdat/pimg/2017_9.png',\n",
       "    'Description': 'GEDI L4B Gridded Prediction Stratum, Version 2, Mission Weeks 19-138',\n",
       "    'Type': 'BROWSE',\n",
       "    'MimeType': 'image/png'},\n",
       "   {'URL': 'https://data.ornldaac.earthdata.nasa.gov/s3credentials',\n",
       "    'Description': 'api endpoint to retrieve temporary credentials valid for same-region direct s3 access',\n",
       "    'Type': 'VIEW RELATED INFORMATION'}]},\n",
       " 'Orderable': 'false',\n",
       " 'DataFormat': 'COG'}"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "COLLECTIONID = collection[0]['concept-id']\n",
    "results = maap.searchGranule(cmr_host='cmr.earthdata.nasa.gov',concept_id=COLLECTIONID)  # COLLECTIONID 'C2244602422-ORNL_CLOUD'\n",
    "print(f'Got {len(results)} results')\n",
    "results[0]['Granule']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3658daf5",
   "metadata": {},
   "source": [
    "## Accessing and Downloading the Granule from ORNL DAAC S3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70e89637",
   "metadata": {},
   "source": [
    "Before downloading, we'll get the collection and file name:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "d1df4352",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GEDI_L4B_Gridded_Biomass\n",
      "GEDI04_B_MW019MW138_02_002_05_R01000M_PS\n"
     ]
    }
   ],
   "source": [
    "granule_ur=results[0]['Granule']['GranuleUR'].split(\".\")\n",
    "collection_name=granule_ur[0]\n",
    "file_name=granule_ur[1]\n",
    "\n",
    "print(collection_name)\n",
    "print(file_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a5cc477",
   "metadata": {},
   "source": [
    "Now we'll proceed to get tempory s3 credentials, and then download the tif file to our workspace:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "b64e74ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_s3_creds(url):\n",
    "    return maap.aws.earthdata_s3_credentials(url)\n",
    "\n",
    "def get_s3_client(s3_cred_endpoint):\n",
    "    creds=get_s3_creds(s3_cred_endpoint)\n",
    "    boto3_session = boto3.Session(\n",
    "            aws_access_key_id=creds['accessKeyId'],\n",
    "            aws_secret_access_key=creds['secretAccessKey'],\n",
    "            aws_session_token=creds['sessionToken']\n",
    "    )\n",
    "    return boto3_session.client(\"s3\")\n",
    "\n",
    "def download_s3_file(s3, bucket, collection_name, file_name):\n",
    "    os.makedirs(\"/projects/gedi_l4b\", exist_ok=True) # create directories, as necessary\n",
    "    download_path=f\"/projects/gedi_l4b/{file_name}.tif\"\n",
    "    s3.download_file(bucket, f\"gedi/{collection_name}/data/{file_name}.tif\", download_path)\n",
    "    return download_path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "17be51d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "s3_cred_endpoint= 'https://data.ornldaac.earthdata.nasa.gov/s3credentials'\n",
    "s3=get_s3_client(s3_cred_endpoint)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "829bb0e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/projects/gedi_l4b/GEDI04_B_MW019MW138_02_002_05_R01000M_PS.tif'"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bucket=\"ornl-cumulus-prod-protected\"\n",
    "download_path=download_s3_file(s3, bucket, collection_name, file_name)\n",
    "download_path"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc99db15",
   "metadata": {},
   "source": [
    "Open the local file using rasterio, and print the shape of the data to verify if the file was read properly:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "bdd8d8fe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(14616, 34704)\n"
     ]
    }
   ],
   "source": [
    "src = rasterio.open(download_path)\n",
    "data = src.read(1)\n",
    "\n",
    "print(data.shape) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3975bc91",
   "metadata": {},
   "source": [
    "## Plot the Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e81e87f",
   "metadata": {},
   "source": [
    "Finally, we'll use matplotlib to visualize our .tif file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "eeeef31f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyplot.imshow(data)\n",
    "pyplot.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.8"
  },
  "vscode": {
   "interpreter": {
    "hash": "399cbf6e48bb89cdd0bd14a04b5698e0be4f18543650a6891ef6d6d6c5ce46cd"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}