diff --git a/Tutorials/SWOTHR_s3Access_real_data_v11.ipynb b/Tutorials/SWOTHR_s3Access_real_data_v11.ipynb new file mode 100644 index 0000000..a3ecf92 --- /dev/null +++ b/Tutorials/SWOTHR_s3Access_real_data_v11.ipynb @@ -0,0 +1,4060 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# SWOT Hydrology Dataset Exploration in the Cloud\n", + "\n", + "## Accessing and Visualizing SWOT Datasets\n", + "\n", + "### Requirement:\n", + "This tutorial can only be run in an **AWS cloud instance running in us-west-2**: NASA Earthdata Cloud data in S3 can be directly accessed via `earthaccess` python library; this access is limited to requests made within the US West (Oregon) (code: `us-west-2`) AWS region.\n", + "\n", + "### Learning Objectives:\n", + "- Access SWOT HR data prodcuts (archived in NASA Earthdata Cloud) within the AWS cloud, without downloading to local machine\n", + "- Visualize accessed data for a quick check\n", + "\n", + "#### SWOT Level 2 KaRIn High Rate Version 1.1 (where available) Datasets:\n", + "\n", + "1. **River Vector Shapefile** - SWOT_L2_HR_RIVERSP_1.1\n", + "\n", + "2. **Lake Vector Shapefile** - SWOT_L2_HR_LAKESP_1.1\n", + "\n", + "3. **Water Mask Pixel Cloud NetCDF** - SWOT_L2_HR_PIXC_1.1\n", + "\n", + "4. **Water Mask Pixel Cloud Vector Attribute NetCDF** - SWOT_L2_HR_PIXCVec_1.1\n", + "\n", + "5. **Raster NetCDF** - SWOT_L2_HR_Raster_1.1\n", + "\n", + "6. **Single Look Complex Data product** - SWOT_L1B_HR_SLC_1.1\n", + "\n", + "_Notebook Author: Cassie Nickles, NASA PO.DAAC (Aug 2023) || Other Contributors: Zoe Walschots (PO.DAAC Summer Intern 2023), Catalina Taglialatela (NASA PO.DAAC), Luis Lopez (NASA NSIDC DAAC)_\n", + "\n", + "_Last updated: 4 Dec 2023_\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Libraries Needed" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + 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root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n setTimeout(load_or_wait, 100);\n } else {\n Bokeh = root.Bokeh;\n bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n root._bokeh_is_initializing = true\n root._bokeh_onload_callbacks = []\n if (!reloading && (!bokeh_loaded || is_dev)) {\n\troot.Bokeh = undefined;\n }\n load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n });\n }\n }\n // Give older versions of the autoload script a head-start to ensure\n // they initialize before we start loading newer version.\n setTimeout(load_or_wait, 100)\n}(window));" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + "if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n", + " 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scripts.forEach( function (oldScript) {\n", + " var newScript = document.createElement(\"script\");\n", + " var attrs = [];\n", + " var nodemap = oldScript.attributes;\n", + " for (var j in nodemap) {\n", + " if (nodemap.hasOwnProperty(j)) {\n", + " attrs.push(nodemap[j])\n", + " }\n", + " }\n", + " attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n", + " newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n", + " oldScript.parentNode.replaceChild(newScript, oldScript);\n", + " });\n", + " if (JS_MIME_TYPE in output.data) {\n", + " toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n", + " }\n", + " output_area._hv_plot_id = id;\n", + " if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n", + " window.PyViz.plot_index[id] = Bokeh.index[id];\n", + " } else {\n", + " window.PyViz.plot_index[id] = null;\n", + " }\n", + " } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var 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!== null) {\n", + " comm.send({event_type: 'server_delete', 'id': server_id});\n", + " return;\n", + " } else if (comm !== null) {\n", + " comm.send({event_type: 'delete', 'id': id});\n", + " }\n", + " delete PyViz.plot_index[id];\n", + " if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n", + " var doc = window.Bokeh.index[id].model.document\n", + " doc.clear();\n", + " const i = window.Bokeh.documents.indexOf(doc);\n", + " if (i > -1) {\n", + " window.Bokeh.documents.splice(i, 1);\n", + " }\n", + " }\n", + "}\n", + "\n", + "/**\n", + " * Handle kernel restart event\n", + " */\n", + "function handle_kernel_cleanup(event, handle) {\n", + " delete PyViz.comms[\"hv-extension-comm\"];\n", + " window.PyViz.plot_index = {}\n", + "}\n", + "\n", + "/**\n", + " * Handle update_display_data messages\n", + " */\n", + "function handle_update_output(event, handle) {\n", + " handle_clear_output(event, {cell: {output_area: handle.output_area}})\n", + " handle_add_output(event, handle)\n", + "}\n", + "\n", + "function register_renderer(events, OutputArea) {\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[0]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " events.on('output_added.OutputArea', handle_add_output);\n", + " events.on('output_updated.OutputArea', handle_update_output);\n", + " events.on('clear_output.CodeCell', handle_clear_output);\n", + " events.on('delete.Cell', handle_clear_output);\n", + " events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n", + "\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " safe: true,\n", + " index: 0\n", + " });\n", + "}\n", + "\n", + "if (window.Jupyter !== undefined) {\n", + " try {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " } catch(err) {\n", + " }\n", + "}\n" + ], + "application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n function JupyterCommManager() {\n }\n\n JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n comm_manager.register_target(comm_id, function(comm) {\n 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var metadata = message.metadata || {comm_id};\n var msg = {content, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n }\n }) \n var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n return comm_promise.then((comm) => {\n comm.send(data, metadata, buffers, disposeOnDone);\n });\n };\n var comm = {\n send: sendClosure\n };\n }\n window.PyViz.comms[comm_id] = comm;\n return comm;\n }\n window.PyViz.comm_manager = new JupyterCommManager();\n \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n var div = document.createElement(\"div\");\n var script = document.createElement(\"script\");\n node.appendChild(div);\n node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n var output_area = handle.output_area;\n var output = handle.output;\n if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n return\n }\n var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n if (id !== undefined) {\n var nchildren = toinsert.length;\n var html_node = toinsert[nchildren-1].children[0];\n html_node.innerHTML = output.data[HTML_MIME_TYPE];\n var scripts = [];\n var nodelist = html_node.querySelectorAll(\"script\");\n for (var i in nodelist) {\n if (nodelist.hasOwnProperty(i)) {\n scripts.push(nodelist[i])\n }\n }\n\n scripts.forEach( function (oldScript) {\n var newScript = document.createElement(\"script\");\n var attrs = [];\n var nodemap = oldScript.attributes;\n for (var j in nodemap) {\n if (nodemap.hasOwnProperty(j)) {\n attrs.push(nodemap[j])\n }\n }\n attrs.forEach(function(attr) { 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handle_clear_output);\n events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n safe: true,\n index: 0\n });\n}\n\nif (window.Jupyter !== undefined) {\n try {\n var events = require('base/js/events');\n var OutputArea = require('notebook/js/outputarea').OutputArea;\n if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import glob\n", + "import os\n", + "import requests\n", + "import s3fs\n", + "import fiona\n", + "import netCDF4 as nc\n", + "import h5netcdf\n", + "import xarray as xr\n", + "import pandas as pd\n", + "import geopandas as gpd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import hvplot.xarray\n", + "import earthaccess\n", + "from earthaccess import Auth, DataCollections, DataGranules, Store" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Earthdata Login\n", + "\n", + "An Earthdata Login account is required to access data, as well as discover restricted data, from the NASA Earthdata system. Thus, to access NASA data, you need Earthdata Login. If you don't already have one, please visit https://urs.earthdata.nasa.gov to register and manage your Earthdata Login account. This account is free to create and only takes a moment to set up. We use `earthaccess` to authenticate your login credentials below." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EARTHDATA_USERNAME and EARTHDATA_PASSWORD are not set in the current environment, try setting them or use a different strategy (netrc, interactive)\n", + "You're now authenticated with NASA Earthdata Login\n", + "Using token with expiration date: 01/07/2024\n", + "Using .netrc file for EDL\n" + ] + } + ], + "source": [ + "auth = earthaccess.login()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "### Single File Access\n", + "\n", + "#### **1. River Vector Shapefiles**\n", + "\n", + "The s3 access link can be found using `earthaccess` data search. Since this collection consists of Reach and Node files, we need to extract only the granule for the Reach file. We do this by filtering for the 'Reach' title in the data link.\n", + "\n", + "Alternatively, Earthdata Search [(see tutorial)](https://nasa-openscapes.github.io/2021-Cloud-Workshop-AGU/tutorials/01_Earthdata_Search.html) can be used to search in a map graphic user interface.\n", + "\n", + "For additional tips on spatial searching of SWOT HR L2 data, see also [PO.DAAC Cookbook - SWOT Chapter tips section](https://podaac.github.io/tutorials/quarto_text/SWOT.html#tips-for-swot-hr-spatial-search).\n", + "\n", + "#### Search for the data of interest" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Granules found: 14\n" + ] + } + ], + "source": [ + "#Retrieves granule from the day we want, in this case by passing to `earthdata.search_data` function the data collection shortname, temporal bounds, and for restricted data one must specify the search count\n", + "river_results = earthaccess.search_data(short_name = 'SWOT_L2_HR_RIVERSP_1.1', \n", + " temporal = ('2023-04-08 00:00:00', '2023-04-22 23:59:59'),\n", + " granule_name = '*Reach*_013_NA*') # here we filter by Reach files (not node), pass #13 and continent code=NA" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Set up an `s3fs` session for Direct Cloud Access\n", + "`s3fs` sessions are used for authenticated access to s3 bucket and allows for typical file-system style operations. Below we create session by passing in the data access information." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "fs_s3 = earthaccess.get_s3fs_session(results=river_results)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "#### Create Fiona session to work with zip and embedded shapefiles in the AWS Cloud\n", + "The native format for this data is a **.zip** file, and we want the **.shp** file within the .zip file, so we will create a Fiona AWS session using the credentials from setting up the s3fs session above to access the shapefiles within the zip files. If we don't do this, the alternative would be to download the data to the cloud environment (e.g. EC2 instance, user S3 bucket) and extract the .zip file there." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "fiona_session=fiona.session.AWSSession(\n", + " aws_access_key_id=fs_s3.storage_options[\"key\"],\n", + " aws_secret_access_key=fs_s3.storage_options[\"secret\"],\n", + " aws_session_token=fs_s3.storage_options[\"token\"]\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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reach_idtimetime_taitime_strp_latp_lonriver_namewsewse_uwse_r_u...p_wid_varp_n_nodesp_dist_outp_lengthp_mafp_dam_idp_n_ch_maxp_n_ch_modp_low_slpgeometry
0774600000137.342535e+087.342536e+082023-04-08T07:18:42Z40.621824-124.244823Eel River2.320100e+009.653000e-023.490000e-02...23702.8059619376.98619194.609276-1.000000e+120410LINESTRING (-124.29069 40.66364, -124.29104 40...
1774600000217.342535e+087.342536e+082023-04-08T07:18:42Z40.542406-124.156177Eel River9.248800e+009.071000e-021.130000e-02...3435.5245129478.83610101.849934-1.000000e+120210LINESTRING (-124.16119 40.58421, -124.16097 40...
2774600000317.342535e+087.342536e+082023-04-08T07:18:42Z40.494638-124.107178Eel River1.970160e+015.754600e-015.683800e-01...1202.5495039553.70710074.871060-1.000000e+120210LINESTRING (-124.13864 40.50871, -124.13829 40...
3774600000417.342535e+087.342536e+082023-04-08T07:18:42Z40.447111-124.021272Eel River3.471650e+011.486718e+011.486691e+01...645.9848155843.42516289.718636-1.000000e+120110LINESTRING (-124.09611 40.46269, -124.09575 40...
4774600000517.342535e+087.342536e+082023-04-08T07:18:42Z40.395990-123.930243Eel River3.229870e+019.148000e-021.638000e-02...1532.6585166073.91010230.484650-1.000000e+120210LINESTRING (-123.95755 40.42295, -123.95719 40...
..................................................................
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360 rows × 127 columns

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" + ], + "text/plain": [ + " reach_id time time_tai time_str p_lat \\\n", + "0 77460000013 7.342535e+08 7.342536e+08 2023-04-08T07:18:42Z 40.621824 \n", + "1 77460000021 7.342535e+08 7.342536e+08 2023-04-08T07:18:42Z 40.542406 \n", + "2 77460000031 7.342535e+08 7.342536e+08 2023-04-08T07:18:42Z 40.494638 \n", + "3 77460000041 7.342535e+08 7.342536e+08 2023-04-08T07:18:42Z 40.447111 \n", + "4 77460000051 7.342535e+08 7.342536e+08 2023-04-08T07:18:42Z 40.395990 \n", + ".. ... ... ... ... ... \n", + "355 78322900143 -1.000000e+12 -1.000000e+12 no_data 50.998910 \n", + "356 78322900153 7.342537e+08 7.342537e+08 2023-04-08T07:21:51Z 51.047442 \n", + "357 78322900173 -1.000000e+12 -1.000000e+12 no_data 50.916115 \n", + "358 78322900183 7.342537e+08 7.342537e+08 2023-04-08T07:21:52Z 51.060235 \n", + "359 78322900211 -1.000000e+12 -1.000000e+12 no_data 50.549433 \n", + "\n", + " p_lon river_name wse wse_u wse_r_u ... \\\n", + "0 -124.244823 Eel River 2.320100e+00 9.653000e-02 3.490000e-02 ... \n", + "1 -124.156177 Eel River 9.248800e+00 9.071000e-02 1.130000e-02 ... \n", + "2 -124.107178 Eel River 1.970160e+01 5.754600e-01 5.683800e-01 ... \n", + "3 -124.021272 Eel River 3.471650e+01 1.486718e+01 1.486691e+01 ... \n", + "4 -123.930243 Eel River 3.229870e+01 9.148000e-02 1.638000e-02 ... \n", + ".. ... ... ... ... ... ... \n", + "355 -119.011806 no_data -1.000000e+12 -1.000000e+12 -1.000000e+12 ... \n", + "356 -119.042215 no_data 3.451806e+02 1.114110e+00 1.110470e+00 ... \n", + "357 -119.036919 no_data -1.000000e+12 -1.000000e+12 -1.000000e+12 ... \n", + "358 -118.938606 no_data -1.000000e+12 -1.000000e+12 -1.000000e+12 ... \n", + "359 -119.062048 Shuswap River -1.000000e+12 -1.000000e+12 -1.000000e+12 ... \n", + "\n", + " p_wid_var p_n_nodes p_dist_out p_length p_maf p_dam_id \\\n", + "0 23702.805 96 19376.986 19194.609276 -1.000000e+12 0 \n", + "1 3435.524 51 29478.836 10101.849934 -1.000000e+12 0 \n", + "2 1202.549 50 39553.707 10074.871060 -1.000000e+12 0 \n", + "3 645.984 81 55843.425 16289.718636 -1.000000e+12 0 \n", + "4 1532.658 51 66073.910 10230.484650 -1.000000e+12 0 \n", + ".. ... ... ... ... ... ... \n", + "355 116183.841 15 59585.535 2935.007230 -1.000000e+12 0 \n", + "356 41059.043 51 30434.699 10168.113068 -1.000000e+12 0 \n", + "357 186564.361 98 39488.857 19642.879384 -1.000000e+12 0 \n", + "358 177029.325 86 56650.527 17161.670624 -1.000000e+12 0 \n", + "359 122.690 50 103956.987 10074.432813 -1.000000e+12 0 \n", + "\n", + " p_n_ch_max p_n_ch_mod p_low_slp \\\n", + "0 4 1 0 \n", + "1 2 1 0 \n", + "2 2 1 0 \n", + "3 1 1 0 \n", + "4 2 1 0 \n", + ".. ... ... ... \n", + "355 1 1 0 \n", + "356 2 1 0 \n", + "357 4 1 0 \n", + "358 4 1 0 \n", + "359 2 1 0 \n", + "\n", + " geometry \n", + "0 LINESTRING (-124.29069 40.66364, -124.29104 40... \n", + "1 LINESTRING (-124.16119 40.58421, -124.16097 40... \n", + "2 LINESTRING (-124.13864 40.50871, -124.13829 40... \n", + "3 LINESTRING (-124.09611 40.46269, -124.09575 40... \n", + "4 LINESTRING (-123.95755 40.42295, -123.95719 40... \n", + ".. ... \n", + "355 LINESTRING (-119.03134 51.00406, -119.03105 51... \n", + "356 LINESTRING (-119.03140 51.09147, -119.03165 51... \n", + "357 LINESTRING (-118.99201 50.99421, -118.99200 50... \n", + "358 LINESTRING (-118.99200 50.99394, -118.99201 50... \n", + "359 LINESTRING (-119.11242 50.54684, -119.11207 50... \n", + "\n", + "[360 rows x 127 columns]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Get the link for the first zip file\n", + "river_link = earthaccess.results.DataGranule.data_links(river_results[0], access='direct')[0]\n", + "\n", + "# We use the zip+ prefix so fiona knows that we are operating on a zip file\n", + "river_shp_url = f\"zip+{river_link}\"\n", + "\n", + "with fiona.Env(session=fiona_session):\n", + " SWOT_HR_shp1 = gpd.read_file(river_shp_url) \n", + "\n", + "#view the attribute table\n", + "SWOT_HR_shp1 " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "#### Quickly plot the SWOT river data" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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danB7FRUVUCgUKpOhqhtnLi8vD5s3b9ZxNfpFoyAHBARg3759+OOPP7Br1y5kZ2dj0KBBKCgo4Dpytre3V1nH3t6+0U6ew8LCIJPJuMnFxaUZu8EPQqEQU6ZMAQD89NNPXG+WTNM0CvLYsWMxdepU+Pj4YOTIkTh+/DgAcH3tAk+PEEREjY4atHr1asjlcm5KS0vTpCTeWbt2LcRiMe7fv489e/bouhy90aLLb+bm5vDx8cH9+/e5qxdPtr65ublPtdKPMzExgaWlpcpkyPz8/PDJJ5/A3Nwc+/bt03U5eqNFQa6oqMCdO3fQsWNHdO7cGQ4ODjh16hT3eWVlJc6dO4dBgwa1uFBD4u7ujoyMDDx48EDXpegNjYK8fPlynDt3DklJSbh69SpeeuklKBQKzJo1CwKBAEuWLEFoaCgOHz6MW7duYfbs2TAzM8P06dO1VT8v1Q1Mk5WVZdAnv5rQ6FWn9PR0BAUFIT8/H7a2thgwYACuXLkCV1dXAMC///1vlJWVYcGCBSgsLOReCVe3+1Km1q1bt7ifNRmV1JCxfi3aob/++gvBwcEQCoX4448/Gh1hlO/UzQN71qIdGjBgAFJTU5GcnIzIyEhdl6MXWJDbIbFYzJ0gPz6wDNMwFuR2qnfv3gAAuVyu20L0BAtyOyWTyTBo0KA27QhQn7Egt1Pnz5/HpUuX4OjoqOtS9AILcjtUVFSEixcvAgCUSqWOq9EPrMusdsjc3Bz9+/dHXl4eJk6cqOty9AJrkdshIyMjdOvWDUlJSbC1tdV1OXqBBbmd2r9/PwCwV8XUxILcTtUNRD506FAdV6If2DFyO/XVV18hKSkJnTt31nUpeoEFuZ2SSCSIiIjQeBwPQ8UOLdoxFmL1sSAzvMCCzPACCzLDCyzIDC+wIDO8wILM8AILMsMLLMgML7AgM7zAgszwAgsywwssyAwvsCAzvMCCzPACCzLDCyzIDC+wIDO8wIKsBw4cOIC5c+einfUA3K6wILdzn3/+OYKCgrBnzx6DHyioMezl03Zs5cqVOHPmDIDaEWfrhmRgnsaC3E6dPXsWmzZtAgDMmjULX3zxBXsZtRFs6AUtIyJER0fj+PHjKC8vh5+fH3JycvDzzz/j3Llz6NevH+zt7bFp0yb06NEDQO3/B127doWNjQ1ycnJw+/btRod44zN188BaZC05ffo0/vzzT4SFhcHPzw/Xr18HAFhbW6OwsBAWFhYQi8XIz89HbGwsevbsCRcXFwwaNAipqanIzc1FQUEBLl68aLAh1gQLshYolUr8+OOP2LVrFwCgoKCA+8zFxQWVlZUQCoXw9/dHXl4ezMzMUF5ejrS0NBw8eBBCoRAmJiZ45ZVX0K9fP13thn7R9ujumlJ3NPj2TqlU0ubNm8nHx4eWLl1KlZWVlJmZ+dRy1dXVdPLkSbKysiIAZGxsTO+99x5du3ZNB1W3P+rmgR0jtxPp6enw8fFBUVERFi1ahE8//VTXJbULbHgyPePs7IygoCAAtdeOAwMDcf/+fR1XpT9YkNsRmUwGoPZKx/nz5xEWFqbjivQHO9lrI/fv30dycjKcnJzw119/wcvLC4MHD1ZZpqKiAiYmJqioqAAA7NmzBz179sQ777zDhvJtSlscsGuCLyd7j/vyyy8JAAEgNzc3AkCffPKJyjJZWVncMhYWFuTs7Mz9e9y4cTR06FAaNmwYRURE6GYndETdPLAWuRUplUr89NNPuHPnDjw8PDBs2DBs2LABX3/9NbeMlZUVAKBjx44q68bHx3M/192WHj9+PPLz8xEVFYW8vDwAtSeF165dM6gTYXWwILei4uJirF+/Hnfv3oWXlxdCQkJUAnvs2DFYW1ujS5cuT93kGDBgAFasWIE1a9ZwYc/Ly8PevXuRkJCA0tJS7N69G46OjizE9WmjvxBq0/dDi8OHD3OHBFKplPsZAE2ePLnRdZVKZaOfy+Vy+v7775tcjk/YdWQdISIQEeLi4iCVSpGfn493330Xf/zxBxwdHTFw4EB06NABSqUS06dPx9ChQ2FkZKTrststtfPQkt+W0NBQAkCLFy/m5hUXF9PChQvJycmJTE1NydPTk7Zv3672NvW9Ra5PeXk5+fr6EgBycHBQ+V8ANHPmTINqZTWhbh6afR05KioKO3fuhK+vr8r8pUuXIiIiAvv378edO3ewdOlSvP322zh69Ghzv0ovFRUVYfv27fjtt99gYmKCTz75BNbW1vDw8ABQ+/AQUDs45KxZs1BTU6PLcvVfc35LiouLqWvXrnTq1CkKDAxUaZG9vLzo/fffV1m+T58+9O6776q1bb60yOfPnyehUEgAaNGiRSqfVVRUUFlZGT18+JC++eYb1ho3Qqst8sKFCzF+/HiMHDnyqc+GDBmCX3/9FRkZGSAinD17FvHx8Rg9enS926qoqIBCoVCZ+ODUqVPcgOjbt29X+czY2BimpqawtrbGnDlz2M2O1qDpb8gPP/xA3t7eVFZWRkT0VItcUVFBM2fOJAAkFovJ2NiY9u3b1+D21q1bp3JmXzfpe4ucmJhIMpmM25+HDx/quiS9pJUWOS0tDYsXL8b+/fthampa7zKfffYZrly5gl9//RXXrl3Dxx9/jAULFuD06dP1Lr969WrI5XJu4ssLlsbGxtybHiKRCN9++62uS+I3TX476q6RikQibgJAAoGARCIRPXr0iIyMjOjYsWMq67322ms0evToVv0N1AcffPABASAjIyPq1asXKZVKSklJodTUVMrPz6djx47RgQMH6OrVq1RVVaXrctslrdyiHjFiBGJjY1XmzZkzB56enli5ciVqampQVVUFoVC1oReJRNzxoiF599138corr6B79+6IiYlB3759ER0dDaD2TZG6vz4SiQTl5eUYO3YsPvvsM3Tp0kWXZeunlv7GPHmMHBgYSF5eXnT27FlKTEykPXv2kKmpqdrXkvnUIhMR1dTUkLe3N/eXDAB5eXmRQCDgjp979eqlcn4wZMgQys/P13Xp7YLWryM35MCBA+jXrx+Cg4PRs2dPhIeHY+PGjXjzzTdb+6v0glAoxMWLF/HOO+9w14pnzZqFffv24datWyAibNq0CR4eHujWrRt69OiB1NRUvPnmm6xnIU20ya+VBvjWIteJiYkhADR48GDavHlzvcskJCTQ6NGjuZbZ09PT4K926KxFZur3zTffAAAuXryI4cOH17tMly5dEBERgY8//hhA7aOedXcAmcaxxzjbiEgkAgCYmppi8ODBiIuLg7u7e73LLlu2DJ07d4azszOIiN0wUQNrkdvI5s2bERgYCCJCeXk5IiIiGl1+ypQp6NevHwuxmliQ24hAIMCff/7JvY9Xd6jBtA4W5DYkFAphbW0NExMTZGRk4MqVK7ouiTdYkNtYeHg4KioqIJVKMWTIEGzYsAE1NTUoKirCggULkJGRoesS9RILchubN28edu/eDRcXF9TU1GD9+vV49dVXYW1tjXPnznEnhYxmWJB1YO7cudizZw86deqEwYMH4/bt23BycoKtrS0iIyN1XZ5eYkHWkU6dOuHs2bPIzc3FnTt3kJ+fjxkzZmDatGm6Lk0vsevIOuTu7o74+HgolUpUV1fD2NhY1yXpLdYitwNCoZCFuIVYkBleYEFmeIEFmeEFFmSGF1iQGV5gQWZ4gQWZ4QUWZIYXWJAZXmBBZniBBZnhBRZkhhdYkBleYEFmeIEFmeEFFmSGF1iQGV5gQWZ4gQWZ4QUWZIYXWJAZXmBB1rGioiJs2LBB12XoPRbkFiAibN++HT169MC7776L0tJSjdZ/8OABAgIC8MEHH+DevXtaqtJAtEX3+ZrQh6EXUlNT6b333qOgoCCVQWwGDx5MK1eurHe4hMcH0rSzs3tqYHVNBp43JFoZnszQERG2bt2KZcuWAYBKh4MWFhaIiorCxYsXcf/+fSxatAiXL1+Gg4MDTp8+je+++w7GxsYwMTFBfn4+AODhw4cwNjbGgQMHMGXKFJ3sE1+wIKuhuroa27Ztw9q1ayEQCODu7o7ExESIRCJs2rQJs2fPRn5+Pv773/8iIiIChw4dQnZ2Ni5dugRLS0sQESQSCcrKyuDs7AxnZ2e4urrCxcUFS5YsgZOTk653Uf+1yd8HDbS3Q4uoqChyd3fnDgFMTU2pZ8+edOzYMSotLX1q+Zs3b9LEiRPJwsKChEIhdezYkcaNG0fPPfccXbt2jcrLy3WwF/pL3TywIDeivLycTE1Nyc/PjwBQ79696eTJk1RdXd3kumVlZVRTU0NXrlyhxMTENqiWn9gxcisoLi5GeXk5rl+/jlWrViE0NFTtwWnqBp0PCAjQZonM/7DLb40oKyvjfp42bRobYakdY0FuhIuLCyQSCQDg+vXrOq6GaQwLchPGjRsHLy8vhIeH67oUphHsGLkJxcXFKCkpQXJysq5LYRrBWuR6HD16FBEREVAqlaipqUFmZiaGDRum67KYRrAW+QlKpRKLFy9GSkoKVq9ejfLyclRVVcHV1VXXpTGNYC3yE0pKSjBmzBgAwPHjx/HPP/+Aaq+367gypjEtCnJYWBgEAgGWLFmiMv/OnTuYOHEiZDIZpFIpBgwYgNTU1JZ8VZuRSqXYsWMHduzYgezsbHTo0AGmpqb49ddfdV0a04hmBzkqKgo7d+6Er6+vyvwHDx5gyJAh8PT0RGRkJGJiYrB27VruBoG+mD9/Pv7++28MHDgQYrEYRUVFkMvlui6LaUhzbhsWFxdT165d6dSpUxQYGEiLFy/mPnv11VdpxowZam+rvLyc5HI5N6WlpbWbW9R1rKysyN3dnc6dO6frUgyOureom9UiL1y4EOPHj8fIkSNV5iuVShw/fhzdunXD6NGjYWdnh4CAABw5cqTBbYWFhUEmk3GTi4tLc0rSqn/9619ITk7G0qVLUVlZyc3PzMxEcXGxDitjOJr+hvzwww/k7e1NZWVlREQqLXJWVhYBIDMzM9qyZQtdv36dwsLCSCAQUGRkZL3b04cWOT09nbp06UICgYAWLFhAvXr1IqlUSgDo9OnTui6P17Ty9FtqairZ2dnRjRs3uHmPBzkjI4MAUFBQkMp6EyZMoGnTprVq4W1twYIFZGtrSxYWFjR06FAyNTUlAOTv709KpVLX5fGWVg4trl27htzcXPj7+0MsFkMsFuPcuXP47LPPIBaLYWNjA7FYjJ49e6qs16NHD725atEQBwcH5OXl4dGjR7hw4QJGjBiBr776CpcvX2YPE7UDGt0QGTFiBGJjY1XmzZkzB56enli5ciVMTEzQr1+/p16kjI+P1/sbCufPnwcAWFlZoaioCEuWLHnqHIHRHY2CLJVK4e3trTLP3NwcNjY23PwVK1bg1VdfxbPPPovhw4cjIiICv/32GyIjI1ut6LZWXFyMCxcucD//8MMPGDFihI6rYh7X6nf2pkyZgh07dmDTpk3w8fHB119/jV9++QVDhgxp7a9qM1KpFBUVFQAAoVCIHj16sMOJdqbFz1rU19LOnTsXc+fObemm241Lly5xPyuVSpw6dQq9evVq8XYfPXoEc3NzCAQCPHr0CNHR0fjnn39QVFSEV155Bd7e3qiqqoJYLGa/OE1gDw2p4YcffoCLiwvy8vJQXl4OobBlf8hOnjyJ3bt348cff4SDgwNcXFwQFRXFfe7m5obQ0FB06dIF5ubmyM7OxqJFi7BgwQJYWlq2dHd4iT00pIa7d+8iLS0NdnZ2ePbZZ9GjR49mbYeIcOTIEYwZMwZHjx6Fh4cHsrOz4ejoCACwsbHB+PHj8dxzz6Gmpgbx8fEwNzdHVlYW1qxZg169erFnPhrAWmQ1PPfcczh9+jRSU1ORmpqKzMxMbNiwAb1794anp6daLfTVq1fx0UcfwcLCAkQEX19fHDhwAPfv30dZWRm2bt0KNzc3ALWBX7BgAWJiYtC9e3dcvXoVf/75J44fP46tW7di4sSJWt5jPdQWF7U10R5viNTU1NDYsWMJAAmFQvL09CQA5OzsTF27dqW9e/dSQkICRUdHU0JCArfew4cPadu2bRQSEkLm5uY0YMAAGj16NIWEhFBGRoZGNVy9epUA0CeffNLKe9e+qZsHAVH7etBWoVBAJpNBLpe3q+PBhw8fwt/fH46OjoiLi4ONjQ3c3d1x+vRpAICHhwcSEhJgZmaGoKAgiMVi5ObmIi4uDi4uLjAxMYGLiwsmT57MPe+sierqagQHB2Py5MkICgpq7d1rt9TNAwuyBpKTkzFlyhTcuHEDUqkUV69exfHjx/HLL7/g1q1bkEgksLOzQ1xcHIDaa+wvvfQShg0bhpEjR8LZ2VnHe6B/WJC1pKioCOPHj4dEIsHbb7+NSZMmqXz+22+/4a+//oJIJELv3r0xevRoyGQyHVWr/9TNAzvZ05CVlRXs7Oy4qw9PmjBhAiZMmKCDygwbu/zWDJaWlrCxscHdu3d1XQrzPyzIzeDo6IiCggLs3r0bWVlZui6HAQtys8yfPx8mJiYAat9wYXSPHSNrQKFQ4K+//sKuXbtQUVGBkSNHon///rouiwELcoOICOHh4di7dy9mzZqFyspKfPzxx/D09ERUVBR8fHzg6uqK4OBgXZfKAOzOXkN++uknAkBDhw4lAOTj40MymYykUin5+vqSUCikH3/8Uac1GgLW0XcLxMTE4I033gBQ+3aLSCSClZUVXnzxRbz33nuoqalBamoqunTpouNKmTosyPW4efMmioqKYGZmhgkTJmDHjh2Qy+Xo0KEDgNqH61mI2xcW5HpMmjQJUqkUIpEIhYWFEIlEXIiZ9oldfquHmZkZiouLYWZmhkePHum6HEYNLMj12LhxI/z8/JCfnw93d3ddl8OogQW5Hn/99ReuX7+O2bNnY8uWLbouh1EDC3I90tPT4e7ujsDAQL3rRdRQsSDXw97eHomJiVi3bp2uS2HUxIL8hNjYWJSWlsLLywsFBQW6LodRE7v89oQVK1YgKioK1tbWmD59uq7LYdTEgvyY1atX448//kCfPn3g7++PrVu36rokRk3s0OJ/iAh37txBt27doFAosGHDBojF7PdcX7AgPyYmJgYJCQkoLCzEnDlzdF0OowEW5P8RCAT4+uuvYWRkhLKyMmRmZqK0tFTXZTFqYkF+zJ07d2BjY4PS0lKIRCJIpVIUFhbquixGDSzIjzE2NkZBQQGMjIyQmJgIpVKJDRs2oKysTNelMU1gQX7MpEmT4O/vDyMjIzx69Ajdu3fHDz/8gLFjx+q6NKYJLMiPCQoKwqVLl2BtbQ2lUom8vDzk5ubi3LlzOHjwoK7LYxrBggygqqoKL774IlJSUgAA5eXlCA0N5YbwlUgkWL58ObvT146xIAPYtm0bDh8+jLy8PPj5+SEnJwerV6+GkZERjhw5AmNjY6SnpyMmJkbXpTINYEEGkJCQgEGDBqG4uBi7d++GSCTiPjM1NYVcLmcP2bdzLMgAxo8fz40TcvXqVZXPunfvDjMzM/Tp0weTJk3C22+/rYsSmSawIAMYN24c1+VrZmamymeWlpa4cuUKzM3NAdQehjw+3gfTPrAg/096ejqsrKxQUlLy1Gc+Pj44fPgwAMDFxQXDhg1DTU1NW5fINIIFGUBOTg68vb1RVFQEOzu7epeRSCR46623kJaWhtLSUi7YTPvAHu8CEBcXh1u3bsHKyuqpkV0ft2TJEmRnZ0MikbCXUtsZFmTUXjc2MjJCUVERjh07hvHjx9e7XJcuXfDTTz+1cXWMOtihBYBBgwbB398fFhYW2LFjBzdcL6M/WJBRO5zCf//7X8hkMgwdOhQ3btzQdUmMhliQ/6d79+4QiUS4cOEC68tCD7EgP8bDwwN2dnZITU1FZWVlk8uXl5ejvLxcZV5GRoa2ymMawU72HrNmzRqMHDkSubm5OHDgAGbOnNngsnFxcRg2bBgePXqEN998ExKJBPn5+cjOzsbRo0chEAjasHKmRR19h4aGEgBavHhxvZ/PmzdP42FnddnRt1KpJHNzc3J0dCQA5OnpSTdv3lRZJjY2loKCgiggIIB8fHwIALm5uREAAkDPPfccZWdnt3ntfKX1jr6joqKwc+dO+Pr61vv5kSNHcPXqVTg6Ojb3K9qcQCCAu7s7YmNjAQB3797FwIEDYWJiAk9PTzg5OSE3Nxf5+fkQCoWoqqrCwoULkZeXh+TkZABAt27dGrypwmhRc35LiouLqWvXrnTq1CkKDAx8qkVOT08nJycnunXrFrm6uupNi0xENGvWLAJAlpaWBIDMzc1JKpVyLW7v3r3J3t6ejh49StXV1dx6ycnJlJycrJOa+UzdPDTrZG/hwoUYP348Ro4c+dRnSqUSISEhWLFiBby8vJrcVkVFBRQKhcqkS5988glmzJjB1VHXV7KrqysGDBiAkJAQZGRkYOLEiSqPe7q6usLV1VVXZRs8jQ8tDhw4gOjo6AafAPvwww8hFouxaNEitbYXFhaGDRs2aFqG1lhbW+Pbb7/F1KlT8dNPP+HevXvIy8tDZmYm9uzZg+HDh+u6RKY+mjTzqampZGdnRzdu3ODmPX5o8c8//5C9vT1lZGRwnzd1aFFeXk5yuZyb0tLS2sWoTnUyMjK4QwsLCwv65ZdfqKqqStdlGQx1Dy00CvLhw4cJAIlEIm4CQAKBgEQiEW3evJn7+fHPhUIhubq6tmrhbSk6OpoA0KhRo2jy5MnUt29fSkhI0HVZBkHdPAiIiNRtvYuLi7kXNOvMmTMHnp6eWLlyJTp27PjU2MyjR49GSEgI5syZg+7duzf5HQqFAjKZDHK5HJaWluqWpnXXrl3DggULEBcXh5KSEtja2mLPnj0NPmDEtA5186DRMbJUKn3qMUdzc3PY2Nhw821sbFQ+NzIygoODg1ohbs/8/f1x9epVJCcnY9SoUUhISMALL7yAnTt34vXXX2c3QHSM3aLWkJubGy5cuAB/f38MGTIE8+bNw7///W9dl2XwNDq0aAvt9dDiSYWFhXj55Zdx4cIFVFZW4vvvv8err74KoZC1Da1J3TywILdATU0NPD09YWtri8TERPTr1w+//vorO8xoRermgZfNR1paGqqqqnDs2DHk5eXhzz//xJIlS5CWltaq3yMSifDRRx+htLQUOTk5MDIyQmpqaqt+B6MmrV8/0VBLL79dv36dhEIhd0u5R48e3M99+vShy5cvt3LFtezs7AgAnTlzRivbN1RavUXdnn3++edQKpXcv+/cuQMA6NChAxITEzFw4ECcPn26Vb9ToVAgNzcXANgDQzrCu+eRt23bhkGDBiEjIwNWVlbw8vLC9u3bce7cOa4vilGjRiEiIgKjR49ule/MzMzE8uXLAaDRt7AZLWqjvxBq09advX/961/cIQYAGjFiRKtun9EOgz20aMgXX3wBS0tLSKVSiMVidmWBZwwmyAKBAGvWrEFVVRWqq6vx4MEDlWNpRr8ZTJABYP/+/ZBIJLC1tUVqaiobtYlHeHey15CSkhLcunULpqamKC8vx8mTJ2FhYaHrsphWYjAtck5ODoDakZsA4Ntvv2U9avKIwQTZ3d0dP/74I9fP8bfffotvvvkGQO3wvYWFhdwwZESEixcv4sMPP+ReKq2ursbatWsRFhbGjq3boza5hqIBbT9Yn5ubSwEBAQSAHBwcaNiwYSqX5Tp16kQAyNnZmZu3YsUKsrCw4N4SiYmJ0UptzNO03h2AvrK1teXuwmVnZyM7OxtA7bt6hYWF3NNr6enpEAgEICKcOXOGGz9k7NixkEqluimeaZDBBRmoDW1eXh4XTlNTUxQWFqJDhw7YtGkTzp49i8mTJ6N///5Yvnw5SkpKMHHiRMydOxcuLi46rp6pV9v8gVBfW7yzd/78ee6wQSAQ0FtvvUU1NTVa+z6m+didvUYMHToU69evB1B7YpeSksIeiNdzBvtfr65bLAB4+eWXdVgJ0xoMMsgFBQU4deoU97xFcHCwjitiWsogg1xVVQWFQgH631teGzdu1HFFTEsZZJAdHBxw8OBBPPPMM7C3t8e6dev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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Simple plot\n", + "fig, ax = plt.subplots(figsize=(7,5))\n", + "SWOT_HR_shp1.plot(ax=ax, color='black')" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# # Another way to plot geopandas dataframes is with `explore`, which also plots a basemap\n", + "# SWOT_HR_shp1.explore()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **2. Lake Vector Shapefiles**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The lake vector shapefiles can be accessed in the same way as the river shapefiles above. \n", + "\n", + "For additional tips on spatial searching of SWOT HR L2 data, see also [PO.DAAC Cookbook - SWOT Chapter tips section](https://podaac.github.io/tutorials/quarto_text/SWOT.html#tips-for-swot-hr-spatial-search)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "#### Search for data of interest" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Granules found: 14\n" + ] + } + ], + "source": [ + "lake_results = earthaccess.search_data(short_name = 'SWOT_L2_HR_LAKESP_1.1', \n", + " temporal = ('2023-04-08 00:00:00', '2023-04-22 23:59:59'),\n", + " granule_name = '*Obs*_013_NA*') # here we filter by files with 'Obs' in the name (This collection has three options: Obs, Unassigned, and Prior), pass #13 and continent code=NA" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Set up an `s3fs` session for Direct Cloud Access\n", + "`s3fs` sessions are used for authenticated access to s3 bucket and allows for typical file-system style operations. Below we create session by passing in the data access information." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "fs_s3 = earthaccess.get_s3fs_session(results=lake_results)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Create Fiona session to work with zip and embedded shapefiles in the AWS Cloud\n", + "The native format for this data is a .zip file, and we want the .shp file within the .zip file, so we will create a Fiona AWS session using the credentials from setting up the s3fs session above to access the shapefiles within the zip files. If we don't do this, the alternative would be to download the data to the cloud environment (e.g. EC2 instance, user S3 bucket) and extract the .zip file there." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "fiona_session=fiona.session.AWSSession(\n", + " aws_access_key_id=fs_s3.storage_options[\"key\"],\n", + " aws_secret_access_key=fs_s3.storage_options[\"secret\"],\n", + " aws_session_token=fs_s3.storage_options[\"token\"]\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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4783245R000005783026394332178322700063;78322700091;78322800011;7832290001...7.342537e+087.342537e+082023-04-08T07:22:01Z344.8320.014...-0.009029-0.009206-0.002157-2.207273-0.082830-0.002465-1.000000e+12ROSS CREEK;EAGLE RIVER;SHUSWAP;LITTLE RIVER;SC...-99999999MULTIPOLYGON (((-119.35814 50.94441, -119.3580...
..................................................................
831783246R0090137830249372;783024935281;712no_data7.342537e+087.342538e+082023-04-08T07:22:13Z1837.2320.563...-0.008546-0.008791-0.002133-2.094712-0.066065-0.002440-1.000000e+12no_data-99999999MULTIPOLYGON (((-118.98292 51.59811, -118.9830...
832783246R0099317830249332871no_data7.342537e+087.342538e+082023-04-08T07:22:14Z1635.5140.325...-0.008539-0.008785-0.002132-2.136184-0.071612-0.002440-1.000000e+12no_data-99999999POLYGON ((-118.98463 51.61215, -118.98453 51.6...
833783246R0107407830243082821no_data7.342537e+087.342538e+082023-04-08T07:22:14Z2094.2955.792...-0.008558-0.008815-0.002135-1.942940-0.048756-0.002438-1.000000e+12no_data-99999999MULTIPOLYGON (((-119.07615 51.67504, -119.0759...
834783246R0109107830256902211no_data7.342537e+087.342538e+082023-04-08T07:22:14Z1996.6700.303...-0.008524-0.008775-0.002132-1.863152-0.041920-0.002443-1.000000e+12no_data-99999999POLYGON ((-118.97489 51.63692, -118.97478 51.6...
835782246R0127967820071012751no_data7.342537e+087.342538e+082023-04-08T07:22:15Z1962.5040.385...-0.008469-0.008730-0.002128-2.104326-0.068847-0.002438-1.000000e+12no_data-99999999POLYGON ((-118.88701 51.66364, -118.88710 51.6...
\n", + "

836 rows × 36 columns

\n", + "
" + ], + "text/plain": [ + " obs_id lake_id overlap n_overlap \\\n", + "0 781229R000006 7810001133 85 1 \n", + "1 782232R000018 7820002572;7820002253 86;80 2 \n", + "2 782243R000013 7820039162 10 1 \n", + "3 782243R015586 7820039162 17 1 \n", + "4 783245R000005 7830263943 32 1 \n", + ".. ... ... ... ... \n", + "831 783246R009013 7830249372;7830249352 81;71 2 \n", + "832 783246R009931 7830249332 87 1 \n", + "833 783246R010740 7830243082 82 1 \n", + "834 783246R010910 7830256902 21 1 \n", + "835 782246R012796 7820071012 75 1 \n", + "\n", + " reach_id time \\\n", + "0 no_data 7.342536e+08 \n", + "1 no_data 7.342536e+08 \n", + "2 no_data 7.342537e+08 \n", + "3 no_data 7.342537e+08 \n", + "4 78322700063;78322700091;78322800011;7832290001... 7.342537e+08 \n", + ".. ... ... \n", + "831 no_data 7.342537e+08 \n", + "832 no_data 7.342537e+08 \n", + "833 no_data 7.342537e+08 \n", + "834 no_data 7.342537e+08 \n", + "835 no_data 7.342537e+08 \n", + "\n", + " time_tai time_str wse wse_u ... load_tidef \\\n", + "0 7.342536e+08 2023-04-08T07:19:21Z 593.993 0.011 ... -0.019138 \n", + "1 7.342536e+08 2023-04-08T07:19:51Z 439.811 0.167 ... -0.016663 \n", + "2 7.342537e+08 2023-04-08T07:21:40Z 341.457 0.003 ... -0.009852 \n", + "3 7.342537e+08 2023-04-08T07:21:48Z 341.513 0.028 ... -0.009454 \n", + "4 7.342537e+08 2023-04-08T07:22:01Z 344.832 0.014 ... -0.009029 \n", + ".. ... ... ... ... ... ... \n", + "831 7.342538e+08 2023-04-08T07:22:13Z 1837.232 0.563 ... -0.008546 \n", + "832 7.342538e+08 2023-04-08T07:22:14Z 1635.514 0.325 ... -0.008539 \n", + "833 7.342538e+08 2023-04-08T07:22:14Z 2094.295 5.792 ... -0.008558 \n", + "834 7.342538e+08 2023-04-08T07:22:14Z 1996.670 0.303 ... -0.008524 \n", + "835 7.342538e+08 2023-04-08T07:22:15Z 1962.504 0.385 ... -0.008469 \n", + "\n", + " load_tideg pole_tide dry_trop_c wet_trop_c iono_c xovr_cal_c \\\n", + "0 -0.018407 -0.002311 -2.164411 -0.074947 -0.003339 -1.000000e+12 \n", + "1 -0.016105 -0.002303 -2.199668 -0.069287 -0.003153 -1.000000e+12 \n", + "2 -0.009920 -0.002187 -2.211506 -0.079803 -0.002515 -1.000000e+12 \n", + "3 -0.009599 -0.002172 -2.209661 -0.079193 -0.002491 -1.000000e+12 \n", + "4 -0.009206 -0.002157 -2.207273 -0.082830 -0.002465 -1.000000e+12 \n", + ".. ... ... ... ... ... ... \n", + "831 -0.008791 -0.002133 -2.094712 -0.066065 -0.002440 -1.000000e+12 \n", + "832 -0.008785 -0.002132 -2.136184 -0.071612 -0.002440 -1.000000e+12 \n", + "833 -0.008815 -0.002135 -1.942940 -0.048756 -0.002438 -1.000000e+12 \n", + "834 -0.008775 -0.002132 -1.863152 -0.041920 -0.002443 -1.000000e+12 \n", + "835 -0.008730 -0.002128 -2.104326 -0.068847 -0.002438 -1.000000e+12 \n", + "\n", + " lake_name p_res_id \\\n", + "0 APPLEGATE RESERVOIR;APPLEGATE LAKE 116 \n", + "1 HILLS CREEK RESERVOIR -99999999 \n", + "2 WHITEMAN CREEK;OKANAGAN LAKE;OKANAGAN -99999999 \n", + "3 WHITEMAN CREEK;OKANAGAN LAKE;OKANAGAN -99999999 \n", + "4 ROSS CREEK;EAGLE RIVER;SHUSWAP;LITTLE RIVER;SC... -99999999 \n", + ".. ... ... \n", + "831 no_data -99999999 \n", + "832 no_data -99999999 \n", + "833 no_data -99999999 \n", + "834 no_data -99999999 \n", + "835 no_data -99999999 \n", + "\n", + " geometry \n", + "0 MULTIPOLYGON (((-123.10728 42.03437, -123.1073... \n", + "1 MULTIPOLYGON (((-122.45387 43.68914, -122.4539... \n", + "2 MULTIPOLYGON (((-119.72285 49.72639, -119.7227... \n", + "3 MULTIPOLYGON (((-119.49606 50.06182, -119.4961... \n", + "4 MULTIPOLYGON (((-119.35814 50.94441, -119.3580... \n", + ".. ... \n", + "831 MULTIPOLYGON (((-118.98292 51.59811, -118.9830... \n", + "832 POLYGON ((-118.98463 51.61215, -118.98453 51.6... \n", + "833 MULTIPOLYGON (((-119.07615 51.67504, -119.0759... \n", + "834 POLYGON ((-118.97489 51.63692, -118.97478 51.6... \n", + "835 POLYGON ((-118.88701 51.66364, -118.88710 51.6... \n", + "\n", + "[836 rows x 36 columns]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Get the link for the first zip file\n", + "lake_link = earthaccess.results.DataGranule.data_links(lake_results[0], access='direct')[0]\n", + "\n", + "# We use the zip+ prefix so fiona knows that we are operating on a zip file\n", + "lake_shp_url = f\"zip+{lake_link}\"\n", + "\n", + "with fiona.Env(session=fiona_session):\n", + " SWOT_HR_shp2 = gpd.read_file(lake_shp_url) \n", + "\n", + "#view the attribute table\n", + "SWOT_HR_shp2" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "#### Quickly plot the SWOT lakes data" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(7,5))\n", + "SWOT_HR_shp2.plot(ax=ax, color='black')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Accessing the remaining files is different than the shp files above.** We do not need to read the shapefiles within a zip file using something like Fiona session (or to download and unzip in the cloud) because the following SWOT HR collections are stored in **netCDF** files in the cloud. For the rest of the products, we will open via `xarray`, not `geopandas`." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "jp-MarkdownHeadingCollapsed": true, + "tags": [] + }, + "source": [ + "#### **3. Water Mask Pixel Cloud NetCDF**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "#### Search for data collection and time of interest\n", + "\n", + "For additional tips on spatial searching of SWOT HR L2 data, see also [PO.DAAC Cookbook - SWOT Chapter tips section](https://podaac.github.io/tutorials/quarto_text/SWOT.html#tips-for-swot-hr-spatial-search)." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Granules found: 164\n" + ] + } + ], + "source": [ + "pixc_results = earthaccess.search_data(short_name = 'SWOT_L2_HR_PIXC_1.1',\n", + " temporal = ('2023-04-22 00:00:00', '2023-04-22 23:59:59'), \n", + " granule_name = '*_498_013_*') # here we filter by cycle=498 and pass=013 " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "#### Set up an `s3fs` session for Direct Cloud Access\n", + "`s3fs` sessions are used for authenticated access to s3 bucket and allows for typical file-system style operations. Below we create session by passing in the data access information." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "fs_s3 = earthaccess.get_s3fs_session(results=pixc_results)\n", + "\n", + "# get link for file 100\n", + "pixc_link = earthaccess.results.DataGranule.data_links(pixc_results[100], access='direct')[0]\n", + "\n", + "s3_file_obj3 = fs_s3.open(pixc_link, mode='rb')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "#### Open data using xarray" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The pixel cloud netCDF files are formatted with three groups titled, \"pixel cloud\", \"tvp\", or \"noise\" (more detail [here](https://podaac-tools.jpl.nasa.gov/drive/files/misc/web/misc/swot_mission_docs/pdd/D-56411_SWOT_Product_Description_L2_HR_PIXC_20200810.pdf)). In order to access the coordinates and variables within the file, a group must be specified when calling xarray open_dataset." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
<xarray.Dataset>\n",
+       "Dimensions:                                (points: 5180594, complex_depth: 2,\n",
+       "                                            num_pixc_lines: 3239)\n",
+       "Coordinates:\n",
+       "    latitude                               (points) float64 ...\n",
+       "    longitude                              (points) float64 ...\n",
+       "Dimensions without coordinates: points, complex_depth, num_pixc_lines\n",
+       "Data variables: (12/57)\n",
+       "    azimuth_index                          (points) float64 ...\n",
+       "    range_index                            (points) float64 ...\n",
+       "    interferogram                          (points, complex_depth) float32 ...\n",
+       "    power_plus_y                           (points) float32 ...\n",
+       "    power_minus_y                          (points) float32 ...\n",
+       "    coherent_power                         (points) float32 ...\n",
+       "    ...                                     ...\n",
+       "    interferogram_qual                     (points) float64 ...\n",
+       "    classification_qual                    (points) float64 ...\n",
+       "    geolocation_qual                       (points) float64 ...\n",
+       "    sig0_qual                              (points) float64 ...\n",
+       "    pixc_line_qual                         (num_pixc_lines) float64 ...\n",
+       "    pixc_line_to_tvp                       (num_pixc_lines) float32 ...\n",
+       "Attributes:\n",
+       "    description:                 cloud of geolocated interferogram pixels\n",
+       "    interferogram_size_azimuth:  3239\n",
+       "    interferogram_size_range:    5526\n",
+       "    looks_to_efflooks:           1.5309342049156023\n",
+       "    num_azimuth_looks:           7.0\n",
+       "    azimuth_offset:              3
" + ], + "text/plain": [ + "\n", + "Dimensions: (points: 5180594, complex_depth: 2,\n", + " num_pixc_lines: 3239)\n", + "Coordinates:\n", + " latitude (points) float64 ...\n", + " longitude (points) float64 ...\n", + "Dimensions without coordinates: points, complex_depth, num_pixc_lines\n", + "Data variables: (12/57)\n", + " azimuth_index (points) float64 ...\n", + " range_index (points) float64 ...\n", + " interferogram (points, complex_depth) float32 ...\n", + " power_plus_y (points) float32 ...\n", + " power_minus_y (points) float32 ...\n", + " coherent_power (points) float32 ...\n", + " ... ...\n", + " interferogram_qual (points) float64 ...\n", + " classification_qual (points) float64 ...\n", + " geolocation_qual (points) float64 ...\n", + " sig0_qual (points) float64 ...\n", + " pixc_line_qual (num_pixc_lines) float64 ...\n", + " pixc_line_to_tvp (num_pixc_lines) float32 ...\n", + "Attributes:\n", + " description: cloud of geolocated interferogram pixels\n", + " interferogram_size_azimuth: 3239\n", + " interferogram_size_range: 5526\n", + " looks_to_efflooks: 1.5309342049156023\n", + " num_azimuth_looks: 7.0\n", + " azimuth_offset: 3" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ds_PIXC = xr.open_dataset(s3_file_obj3, group = 'pixel_cloud', engine='h5netcdf')\n", + "ds_PIXC" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "#### Simple plot of the results" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# This could take a few minutes to plot\n", + "plt.scatter(x=ds_PIXC.longitude, y=ds_PIXC.latitude, c=ds_PIXC.height)\n", + "plt.colorbar().set_label('Height (m)')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **4. Water Mask Pixel Cloud Vector Attribute NetCDF**\n", + "\n", + "#### Search for data of interest" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Granules found: 100\n" + ] + } + ], + "source": [ + "pixcvec_results = earthaccess.search_data(short_name = 'SWOT_L2_HR_PIXCVEC_1.1', \n", + " temporal = ('2023-04-08 00:00:00', '2023-04-22 23:59:59'), \n", + " granule_name = '*_498_013_*') # here we filter by cycle=498 and pass=013 " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Set up an `s3fs` session for Direct Cloud Access\n", + "`s3fs` sessions are used for authenticated access to s3 bucket and allows for typical file-system style operations. Below we create session by passing in the data access information." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "fs_s3 = earthaccess.get_s3fs_session(results=pixcvec_results)\n", + "\n", + "# get link for file 0\n", + "pixcvec_link = earthaccess.results.DataGranule.data_links(pixcvec_results[0], access='direct')[0]\n", + "\n", + "s3_file_obj4 = fs_s3.open(pixcvec_link, mode='rb')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Open data using xarray" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
<xarray.Dataset>\n",
+       "Dimensions:               (points: 11174047, nchar_reach_id: 11,\n",
+       "                           nchar_node_id: 14, nchar_lake_id: 10,\n",
+       "                           nchar_obs_id: 13)\n",
+       "Dimensions without coordinates: points, nchar_reach_id, nchar_node_id,\n",
+       "                                nchar_lake_id, nchar_obs_id\n",
+       "Data variables:\n",
+       "    azimuth_index         (points) int32 ...\n",
+       "    range_index           (points) int32 ...\n",
+       "    latitude_vectorproc   (points) float64 ...\n",
+       "    longitude_vectorproc  (points) float64 ...\n",
+       "    height_vectorproc     (points) float32 ...\n",
+       "    reach_id              (points, nchar_reach_id) |S1 ...\n",
+       "    node_id               (points, nchar_node_id) |S1 ...\n",
+       "    lake_id               (points, nchar_lake_id) |S1 ...\n",
+       "    obs_id                (points, nchar_obs_id) |S1 ...\n",
+       "    ice_clim_f            (points) int8 ...\n",
+       "    ice_dyn_f             (points) int8 ...\n",
+       "Attributes: (12/45)\n",
+       "    Conventions:                     CF-1.7\n",
+       "    title:                           Level 2 KaRIn high rate pixel cloud vect...\n",
+       "    short_name:                      L2_HR_PIXCVec\n",
+       "    institution:                     JPL\n",
+       "    source:                          Level 1B KaRIn High Rate Single Look Com...\n",
+       "    history:                         2023-09-07T04:43:11.652934Z: Creation\n",
+       "    ...                              ...\n",
+       "    xref_prior_river_db_file:        \n",
+       "    xref_prior_lake_db_file:         SWOT_LakeDatabase_Cal_013_20000101T00000...\n",
+       "    xref_reforbittrack_files:        SWOT_RefOrbitTrackTileBoundary_Cal_20000...\n",
+       "    xref_param_l2_hr_laketile_file:  SWOT_Param_L2_HR_LakeTile_20000101T00000...\n",
+       "    ellipsoid_semi_major_axis:       6378137.0\n",
+       "    ellipsoid_flattening:            0.0033528106647474805
" + ], + "text/plain": [ + "\n", + "Dimensions: (points: 11174047, nchar_reach_id: 11,\n", + " nchar_node_id: 14, nchar_lake_id: 10,\n", + " nchar_obs_id: 13)\n", + "Dimensions without coordinates: points, nchar_reach_id, nchar_node_id,\n", + " nchar_lake_id, nchar_obs_id\n", + "Data variables:\n", + " azimuth_index (points) int32 ...\n", + " range_index (points) int32 ...\n", + " latitude_vectorproc (points) float64 ...\n", + " longitude_vectorproc (points) float64 ...\n", + " height_vectorproc (points) float32 ...\n", + " reach_id (points, nchar_reach_id) |S1 ...\n", + " node_id (points, nchar_node_id) |S1 ...\n", + " lake_id (points, nchar_lake_id) |S1 ...\n", + " obs_id (points, nchar_obs_id) |S1 ...\n", + " ice_clim_f (points) int8 ...\n", + " ice_dyn_f (points) int8 ...\n", + "Attributes: (12/45)\n", + " Conventions: CF-1.7\n", + " title: Level 2 KaRIn high rate pixel cloud vect...\n", + " short_name: L2_HR_PIXCVec\n", + " institution: JPL\n", + " source: Level 1B KaRIn High Rate Single Look Com...\n", + " history: 2023-09-07T04:43:11.652934Z: Creation\n", + " ... ...\n", + " xref_prior_river_db_file: \n", + " xref_prior_lake_db_file: SWOT_LakeDatabase_Cal_013_20000101T00000...\n", + " xref_reforbittrack_files: SWOT_RefOrbitTrackTileBoundary_Cal_20000...\n", + " xref_param_l2_hr_laketile_file: SWOT_Param_L2_HR_LakeTile_20000101T00000...\n", + " ellipsoid_semi_major_axis: 6378137.0\n", + " ellipsoid_flattening: 0.0033528106647474805" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ds_PIXCVEC = xr.open_dataset(s3_file_obj4, decode_cf=False, engine='h5netcdf')\n", + "ds_PIXCVEC" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Simple plot" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "pixcvec_htvals = ds_PIXCVEC.height_vectorproc.compute()\n", + "pixcvec_latvals = ds_PIXCVEC.latitude_vectorproc.compute()\n", + "pixcvec_lonvals = ds_PIXCVEC.longitude_vectorproc.compute()\n", + "\n", + "#Before plotting, we set all fill values to nan so that the graph shows up better spatially\n", + "pixcvec_htvals[pixcvec_htvals > 15000] = np.nan\n", + "pixcvec_latvals[pixcvec_latvals > 80] = np.nan\n", + "pixcvec_latvals[pixcvec_latvals < -80] = np.nan\n", + "pixcvec_lonvals[pixcvec_lonvals > 180] = np.nan\n", + "pixcvec_lonvals[pixcvec_lonvals < -180] = np.nan" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+       "    Conventions:                   CF-1.7\n",
+       "    title:                         Level 2 KaRIn High Rate Raster Data Product\n",
+       "    source:                        Ka-band radar interferometer\n",
+       "    history:                       2023-09-13T20:22:58Z : Creation\n",
+       "    platform:                      SWOT\n",
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\n", + "" + ], + "text/plain": [ + ":Image [x,y] (wse)" + ] + }, + "execution_count": 39, + "metadata": { + "application/vnd.holoviews_exec.v0+json": { + "id": "p1002" + } + }, + "output_type": "execute_result" + } + ], + "source": [ + "ds_raster.wse.hvplot.image(y='y', x='x')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **6. SLC** " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Search for data collection and time of interest\n", + "\n", + "For additional tips on spatial searching of SWOT HR L2 data, see also [PO.DAAC Cookbook - SWOT Chapter tips section](https://podaac.github.io/tutorials/quarto_text/SWOT.html#tips-for-swot-hr-spatial-search)." + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Granules found: 164\n" + ] + } + ], + "source": [ + "slc_results = earthaccess.search_data(short_name = 'SWOT_L1B_HR_SLC_1.1',\n", + " temporal = ('2023-04-22 00:00:00', '2023-04-22 23:59:59'), \n", + " granule_name = '*_498_013_*') # here we filter by cycle=498 and pass=013 with wildcards" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Set up an `s3fs` session for Direct Cloud Access\n", + "`s3fs` sessions are used for authenticated access to s3 bucket and allows for typical file-system style operations. Below we create session by passing in the data access information." + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "fs_s3 = earthaccess.get_s3fs_session(results=slc_results)\n", + "\n", + "# get link for file \n", + "slc_link = earthaccess.results.DataGranule.data_links(slc_results[0], access='direct')[0]\n", + "\n", + "s3_file_obj6 = fs_s3.open(slc_link, mode='rb')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Open data using xarray\n", + "The L1B_HR_SLC product file contains five NetCDF data group called the slc, xfactor, noise, tvp, and grdem groups. More info can be found in the [product description document within the dataset table](https://podaac.jpl.nasa.gov/SWOT?tab=datasets) for each group." + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "Dimensions:      (num_lines: 17954, num_pixels: 4630, complex_depth: 2)\n",
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+       "Data variables:\n",
+       "    slc_plus_y   (num_lines, num_pixels, complex_depth) float32 ...\n",
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The observations are offered through a range of data products including river and lake vector data in shapefiles, and raster, pixel cloud, and pixel vector data in netCDF. The shapefile products will also contain estimates of river discharge and lake storage change. In this pre-meeting workshop, participants will be introduced to SWOT and the various ways to access and utilize its data products, including via cloud computing, local download, and data transformation tools. Participants will be able to utilize a provided cloud computing environment accessed via personal laptops, or their own laptop’s compute power to explore SWOT data using data recipes by PO.DAAC, NASA’s Physical Oceanography Data Active Archive Center. No prior cloud computing experience is necessary. We welcome all to come and see how SWOT data could augment existing workflows or initiate new, innovative science and applications! The data tutorials at the workshop will use Python, but no prior experience is needed. +### Additional SWOT Resources + +- [PO.DAAC Cookbook: SWOT Chapter](https://podaac.github.io/tutorials/quarto_text/SWOT.html) - additional tutorials & tips +- [SWOT Community GitHub](https://github.com/SWOT-community/SWOT-OpenToolkit) - more community contributions +- [SWOT Product Description Documents](https://podaac.jpl.nasa.gov/SWOT?tab=datasets-information§ions=about) - pdfs embedded in the table ## Acknowledgements diff --git a/prerequisites.md b/prerequisites.md index b3ce9a9..6ab9e43 100644 --- a/prerequisites.md +++ b/prerequisites.md @@ -6,11 +6,12 @@ title: Prerequisites ### 1. Earthdata Login Account -An Earthdata Login account is required to access data, as well as discover restricted data, from the NASA Earthdata system. Thus, to access NASA data, you need Earthdata Login. Please visit https://urs.earthdata.nasa.gov to register and manage your Earthdata Login account. This account is free to create and only takes a moment to set up. Please remember your username and password! +An Earthdata Login account is required to access data, as well as discover restricted data, from the NASA Earthdata system. Thus, to access NASA data, you need Earthdata Login. Please visit [https://urs.earthdata.nasa.gov](https://urs.earthdata.nasa.gov) to register and manage your Earthdata Login account. This account is free to create and only takes a moment to set up. Please remember your username and password! ### 2. GitHub Account -A GitHub account is required to gain access to the provided 2i2c cloud computing platform. Please visit https://github.com/join to register and create a free GitHub account. There was an opportunity to send in your GitHub username when you registered for the workshop, if you did not do so, please email cassandra.l.nickles@jpl.nasa.gov with your GitHub username and mention you are a participant for this workshop. +A GitHub account is required to gain access to the provided 2i2c cloud computing platform. Please visit [https://github.com/join](https://github.com/join) to register and create a free GitHub account. There was an opportunity to send in your GitHub username when you registered for the workshop, if you did not do so, please email cassandra.l.nickles@jpl.nasa.gov with your GitHub username and mention you are a participant for this workshop. ### 3. Laptop or tablet + Participation in the exercises requires a laptop or tablet. Yes, a tablet works too! All participants will have access to a 2i2c Jupyter Lab instance running in AWS us-west 2. diff --git a/schedule.md b/schedule.md index b4362b9..7248a70 100644 --- a/schedule.md +++ b/schedule.md @@ -4,7 +4,7 @@ title: Schedule **The Data Access Workshop for NASA’s SWOT Satellite will take place on Tuesday, February 13th from 9:00-12:30**. -**Note,** hands-on exercises will be executed from a **Jupyter Lab instance in 2i2c.** [Click here to deploy the instance]() and simultaneously clone this GitHub repository to follow along with the tutorials. Please pass along your GitHub Username to get access. +**Note,** hands-on exercises will be executed from a **Jupyter Lab instance in 2i2c.** [Click here to deploy the instance](https://openscapes.2i2c.cloud/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fpodaac%2F2024-SWOT-Hydro-Workshop&urlpath=lab%2Ftree%2F2024-SWOT-Hydro-Workshop%2Findex.md&branch=main) and simultaneously clone this GitHub repository to follow along with the tutorials. Please pass along your GitHub Username to get access. ## Workshop Schedule