{ "cells": [ { "cell_type": "markdown", "id": "c01a4eec-c0af-4dcd-95e9-3a9fb0aba166", "metadata": {}, "source": [ "# ICESat-02 ATL03 Subset and Visualize\n", "\n", "Authors: Sumant Jha (MSFC/USRA), Samuel Ayers (UAH), Alex Mandel (Development Seed), Aimee Barciauskas (Development Seed)\n", "\n", "Date: March 6, 2023\n", "\n", "Description: In this tutorial, we will search for ATL03 data within the NASA CMR. We will then read and visualize the data structure of a granule, create a subset and data frames, and visualize the photon heights." ] }, { "cell_type": "markdown", "id": "064dc9f3-8621-4b1e-8246-4c244d369a56", "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": "4ac294fb", "metadata": {}, "source": [ "## About the Data\n", "\n", "ATLAS/ICESat-2 L2A Global Geolocated Photon Data, Version 5\n", "\n", "\"This data set [ATL03] contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03.\" (Source: [ATL03 Dataset Landing Page](https://nsidc.org/data/atl03/versions/5))" ] }, { "cell_type": "markdown", "id": "4b642af1-b3fa-4b6b-8275-c4047c7f11ad", "metadata": {}, "source": [ "## Additional Resources\n", "- [ATL03 Version 5 User Guide](https://nsidc.org/sites/default/files/atl03-v005-userguide_1.pdf)\n", "- [Earthdata Search](https://search.earthdata.nasa.gov/search?q=ATL03)" ] }, { "cell_type": "markdown", "id": "82823076", "metadata": {}, "source": [ "## Importing and Installing Packages" ] }, { "cell_type": "markdown", "id": "178a2421", "metadata": {}, "source": [ "Required packages:" ] }, { "cell_type": "markdown", "id": "a6302092", "metadata": { "tags": [] }, "source": [ "You will need to install the following required packages if not already present in your working environment: \n", "maap-py, \n", "pandas, \n", "geopandas, \n", "folium, \n", "shapely, \n", "h5glance, \n", "h5py" ] }, { "cell_type": "code", "execution_count": 1, "id": "5877acc2-9813-4d8f-a153-efc819229988", "metadata": {}, "outputs": [], "source": [ "# ! pip install geopandas\n", "# ! pip install folium\n", "# ! pip install h5glance" ] }, { "cell_type": "code", "execution_count": 2, "id": "44746230", "metadata": {}, "outputs": [], "source": [ "# Import the MAAP package\n", "from maap.maap import MAAP\n", "\n", "# Invoke the MAAP constructor using the maap_host argument\n", "maap = MAAP(maap_host='api.maap-project.org')\n", "\n", "# Import pandas dataframe\n", "import pandas as pd\n", "\n", "# Import libraries needed for visualizing data spatial extent\n", "import geopandas as gpd\n", "import folium\n", "from shapely.geometry import Polygon,Point\n", "\n", "# Import H5glance to interactively explore H5 file in notebook\n", "from h5glance import H5Glance\n", "\n", "# Import H5py to read h5 file\n", "import h5py\n", "\n", "# Import os to create a new directory\n", "import os" ] }, { "cell_type": "markdown", "id": "13f4a0af", "metadata": {}, "source": [ "## Decide on a Subset of ATL03 Data\n", "First, we will create a subset using a spatial extent and date range before visualizaing using folium. For this tutorial, we will focus on a very small area over Yosemite National Park and use a temporal range of one day." ] }, { "cell_type": "code", "execution_count": 3, "id": "ac73de13", "metadata": {}, "outputs": [], "source": [ "# Create a variable for short name of ATL03 data\n", "short_name = 'ATL03'\n", "\n", "# Create Latitude, Longitude list.\n", "lat_coords = [37.700057,37.700057,37.758166,37.758166,37.700057]\n", "lon_coords = [-119.680359,-119.680359,-119.538910,-119.538910,-119.680359]\n", "\n", "# Create bounding box\n", "spatial_extent = [lon_coords[0],lat_coords[0],lon_coords[2],lat_coords[2]]\n", "\n", "# Reformat bounding box to work with NASA CMR API\n", "spatial_extent = ','.join(str(coords) for coords in spatial_extent)\n", "\n", "#Provide date range. It is just 1 day. \n", "date_range = ['2021-02-02','2022-02-03']\n", "\n", "# For folium purpose, provide the map center\n", "map_center = [37.729139,-119.609670]\n", "\n", "# Convert to AOI for visualizaton with folium\n", "polygon_geom = Polygon(zip(lon_coords, lat_coords))\n", "\n", "# Provide relevant Coordinate Reference System\n", "crs = 'epsg:4326'\n", "\n", "# Convert to Geodataframe and back to list in that specific reference system\n", "AOI = gpd.GeoDataFrame(index=[0], crs=crs, geometry=[polygon_geom])\n", "AOI_bbox = AOI.bounds.iloc[0].to_list()" ] }, { "cell_type": "code", "execution_count": 4, "id": "cefb1b8d", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Make this Notebook Trusted to load map: File -> Trust Notebook
" ], "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Visualize the spatial extent using folium.\n", "m = folium.Map(map_center, zoom_start=12, tiles='OpenStreetMap')\n", "folium.GeoJson(AOI).add_to(m)\n", "folium.LatLngPopup().add_to(m)\n", "m" ] }, { "cell_type": "markdown", "id": "0d3302d1", "metadata": {}, "source": [ "## Search for Granules\n", "We will now search for granules in NASA's CMR given our spatial extent and date range, then print the number of granules available." ] }, { "cell_type": "code", "execution_count": 5, "id": "0674f479", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "104\n" ] } ], "source": [ "# Provide the name of cmr host to use with maap py\n", "nasa_cmr_host = \"cmr.earthdata.nasa.gov\"\n", "# Search granule using maap-py using subset criteria identified earlier.\n", "data = maap.searchGranule(cmr_host=nasa_cmr_host,short_name = short_name, bounding_box = spatial_extent,temporal= date_range,limit=1000)\n", "# Check to see if the granule search was successfull in finding data within spatial and temporal extent\n", "print(len(data))" ] }, { "cell_type": "markdown", "id": "0bd4dba0-6640-496e-b246-cf686c22ec8e", "metadata": {}, "source": [ "Let's create a new data directory and use maap-py's getData functon to extract the first H5 file. We will then print the name of the extracted file." ] }, { "cell_type": "code", "execution_count": 6, "id": "1864909c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "./data/ATL03_20210202191800_06231006_005_01.h5\n" ] } ], "source": [ "# set data directory\n", "dataDir = \"./data\"\n", "\n", "# check if directory exists -> if directory doesn't exist, directory is created\n", "if not os.path.exists(dataDir):\n", " os.mkdir(dataDir)\n", "\n", "# download and extract the resource\n", "ice_data = data[0].getData(dataDir)\n", "print(ice_data)" ] }, { "cell_type": "markdown", "id": "808f65a6", "metadata": {}, "source": [ "## Read the H5 File\n", "\n", "Let's read in the H5 file to understand the data structure. There are two ways to do this. We can just list keys and then go forward exploring each key one by one..." ] }, { "cell_type": "code", "execution_count": 7, "id": "7d6b2811", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['METADATA',\n", " 'ancillary_data',\n", " 'atlas_impulse_response',\n", " 'ds_surf_type',\n", " 'ds_xyz',\n", " 'gt1l',\n", " 'gt1r',\n", " 'gt2l',\n", " 'gt2r',\n", " 'gt3l',\n", " 'gt3r',\n", " 'orbit_info',\n", " 'quality_assessment']" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Open the H5 file and list the keys\n", "ice_file = h5py.File(ice_data,'r')\n", "list(ice_file.keys())" ] }, { "cell_type": "markdown", "id": "b61e0a3e", "metadata": { "tags": [] }, "source": [ "... or use the h5glance package to interactively list various keys, sub-keys and variables.\n", "\n", "H5Glance lists all the keys and sub-keys and allows for the copying of path variables on the fly, all from within the Jupyter Notebook. \n", "Note: In the web version of this notebook which is shown here, not all sub-fields will be listed. But they can be accessed when using a Jupyter Notebook running on ADE or local machines." ] }, { "cell_type": "code", "execution_count": 8, "id": "1b717c72", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
" ], "text/plain": [ "./data/ATL03_20210202191800_06231006_005_01.h5/ (47 attributes)\n", "├METADATA\t(9 children) (3 attributes)\n", "├ancillary_data\t(34 children) (2 attributes)\n", "├atlas_impulse_response\t(2 children) (1 attributes)\n", "├ds_surf_type\t[int32: 5] (12 attributes)\n", "├ds_xyz\t[int32: 3] (12 attributes)\n", "├gt1l\t(5 children) (7 attributes)\n", "├gt1r\t(5 children) (7 attributes)\n", "├gt2l\t(5 children) (7 attributes)\n", "├gt2r\t(5 children) (7 attributes)\n", "├gt3l\t(5 children) (7 attributes)\n", "├gt3r\t(5 children) (7 attributes)\n", "├orbit_info\t(7 children) (2 attributes)\n", "└quality_assessment\t(9 children) (1 attributes)" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "H5Glance(ice_file)" ] }, { "cell_type": "markdown", "id": "2ec6250d", "metadata": {}, "source": [ "## Subset the Data by Required Columns\n", "\n", "In this case, we will need Latitude, Longitude, Photon Height and Along Track Distance. We are using the copied path from the data tree generated by H5Glance above.\n", "\n", "Use h5py to read file and variables from the copied path." ] }, { "cell_type": "code", "execution_count": 9, "id": "b424f53f", "metadata": {}, "outputs": [], "source": [ "with h5py.File(ice_data,'r') as f:\n", " gt1l_lat = f['/gt1l/heights/lat_ph'][:]\n", " gt1l_lon = f['/gt1l/heights/lon_ph'][:]\n", " gt1l_height = f['/gt1l/heights/h_ph'][:]\n", " gt1l_dist_ph = f['/gt1l/heights/dist_ph_along'][:]" ] }, { "cell_type": "markdown", "id": "48848f25", "metadata": {}, "source": [ "## Show the Subset Data in a Dataframe\n", "1. By using the Pandas module:" ] }, { "cell_type": "code", "execution_count": 10, "id": "b952b2cf", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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LatitudeLongitudePhoton_HeightAlong_track_distance
059.482065-115.906874611.88787816.894447
159.482065-115.906877580.08410616.980614
259.482064-115.906882527.96209717.122099
359.482063-115.906885491.03613317.222527
459.482059-115.906875616.91992217.593958
...............
3656186833.011390-119.75230369.0658654.154013
3656186933.011382-119.752316-16.5013545.156162
3656187033.011380-119.752329-108.5629815.470425
3656187133.011376-119.752317-17.9472055.871534
3656187233.011375-119.752319-37.4890025.938596
\n", "

36561873 rows × 4 columns

\n", "
" ], "text/plain": [ " Latitude Longitude Photon_Height Along_track_distance\n", "0 59.482065 -115.906874 611.887878 16.894447\n", "1 59.482065 -115.906877 580.084106 16.980614\n", "2 59.482064 -115.906882 527.962097 17.122099\n", "3 59.482063 -115.906885 491.036133 17.222527\n", "4 59.482059 -115.906875 616.919922 17.593958\n", "... ... ... ... ...\n", "36561868 33.011390 -119.752303 69.065865 4.154013\n", "36561869 33.011382 -119.752316 -16.501354 5.156162\n", "36561870 33.011380 -119.752329 -108.562981 5.470425\n", "36561871 33.011376 -119.752317 -17.947205 5.871534\n", "36561872 33.011375 -119.752319 -37.489002 5.938596\n", "\n", "[36561873 rows x 4 columns]" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Write latitude, longitude, photon height and along track distance for gt1l to a dataframe\n", "gt1l_df = pd.DataFrame({'Latitude': gt1l_lat, 'Longitude': gt1l_lon, 'Photon_Height': gt1l_height,'Along_track_distance':gt1l_dist_ph})\n", "gt1l_df" ] }, { "cell_type": "markdown", "id": "1b3a00b5", "metadata": {}, "source": [ "2. By using the Geopandas module: \n", "\n", "Create geopandas dataframe with a column for point locations in the geometry column, and other relevant variables." ] }, { "cell_type": "code", "execution_count": 11, "id": "7f5a91a2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Latitude Longitude Photon_Height Along_track_distance \\\n", "0 59.482065 -115.906874 611.887878 16.894447 \n", "1 59.482065 -115.906877 580.084106 16.980614 \n", "2 59.482064 -115.906882 527.962097 17.122099 \n", "3 59.482063 -115.906885 491.036133 17.222527 \n", "4 59.482059 -115.906875 616.919922 17.593958 \n", "\n", " geometry \n", "0 POINT (-115.90687 59.48207) \n", "1 POINT (-115.90688 59.48206) \n", "2 POINT (-115.90688 59.48206) \n", "3 POINT (-115.90689 59.48206) \n", "4 POINT (-115.90687 59.48206) \n" ] } ], "source": [ "geometry = gpd.points_from_xy(gt1l_lon, gt1l_lat)\n", "data = {'Latitude': gt1l_lat, 'Longitude': gt1l_lon, 'Photon_Height': gt1l_height,'Along_track_distance':gt1l_dist_ph}\n", "gdf = gpd.GeoDataFrame(data,geometry=geometry, crs='EPSG:4326')\n", "\n", "# View the resulting geopandas dataframe\n", "print(gdf.head())" ] }, { "cell_type": "markdown", "id": "09272525", "metadata": {}, "source": [ "## Visualize Photon Heights\n", "Finally, we'll visualize the photon heights with respect to along track distance for this H5 file using inputs from the geodataframe:" ] }, { "cell_type": "code", "execution_count": 12, "id": "49248d76", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "fig, ax = plt.subplots(figsize=(14, 4))\n", "gdf.Photon_Height.plot(ax=ax, ls='', marker='.', ms=0.01)\n", "ax.set_xlabel('Along track distance (m)', fontsize=12);\n", "ax.set_ylabel('Photon Height (m)', fontsize=12)\n", "ax.set_title('ICESat-2 ATL03', fontsize=14)\n", "ax.tick_params(axis='both', which='major', labelsize=12)" ] } ], "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": "3.10.8" } }, "nbformat": 4, "nbformat_minor": 5 }