Contents

Data integration with ICESat-2 - Part I

Data integration with ICESat-2 - Part I

Credits

  • Zach Fair

  • Ian Joughin

  • Tasha Snow

Learning Objectives

Goals

  • Identify and locate non-ICESat-2 data sets

  • Acquire data from the cloud or via download

  • Open data in pandas and xarray and basic functioning of DataFrames

Key Takeaway

By the end of this tutorial, you will be able to visualize Cloud Optimized Geotiffs with ICESat-2 and ATM data.

For this tutorial, feel free to run the code along with us as we live code by downsizing the zoom window and splitting your screen (or using two screens). Or you can simply watch the zoom walkthrough. Don’t worry if you fall behind on the code. The notebook is standalone and you can easily run the code at your own pace another time to catch anything you missed.

We will have one exercise you can type into a notebook, or figure out in a separate document. We will also ask some questions that you can responsd to in the tutorial Slack channel.

Computing environment

We’ll be using the following open source Python libraries in this notebook:

# Suppress library deprecation warnings
import logging
logging.captureWarnings(True)

import ipyleaflet
from ipyleaflet import Map, GeoData, LayersControl,Rectangle, basemaps, basemap_to_tiles, TileLayer, SplitMapControl, Polygon

import ipywidgets
import datetime
import re

# %matplotlib widget
import satsearch
from satsearch import Search
import geopandas as gpd
import ast
import pandas as pd
import geoviews as gv
import hvplot.pandas
from ipywidgets import interact
from IPython.display import display, Image
import intake # if you've installed intake-STAC, it will automatically import alongside intake
import xarray as xr
import matplotlib.pyplot as plt
import boto3
import rasterio as rio
from rasterio.session import AWSSession
from rasterio.plot import show
import rioxarray as rxr
from dask.utils import SerializableLock
import os
import hvplot.xarray
import numpy as np
from pyproj import Proj, transform