Updates to intro notebook

* Move challenges about data use to after overview of missions.
* Include references to other companion notebooks.

Author: trey-stafford

notebooks/0_introduction.ipynb

@@ -30,12 +30,6 @@
     "\n",
     "In 2003, NASA launched the Ice, Cloud and Land Elevation Satellite mission with the Geoscience Laser Altimeter System (ICESat/GLAS) instrument onboard. Over the following six years, ICESat/GLAS collected valuable ice thickness data in the Polar Regions. Unfortunately, the ICESat/GLAS mission ended in 2009 before a follow-up mission could be launched. An airborne campaign called Operation IceBridge was funded to fill the gap and continue ice thickness measurements. Between 2009 and 2019, Operation IceBridge flew numerous campaigns over Greenland, the Antarctic ice sheets, and sea ice in the Arctic and Southern Ocean. In September 2018, ICESat-2 was launched to continue NASA's collection of ice, cloud and land elevation data.\n",
     "\n",
-    "The wealth of data from these three missions, as well as from the pre-IceBridge airborne altimetry missions, presents an opportunity to study the evolution of ice thickness over several decades. However, combining data from these missions presents several challenges:\n",
-    "* Data from the Airborne Topographic Mapper (ATM) flown during the IceBridge campaigns is stored in four different file formats. ICESat/GLAS and ICESat-2 data are also in different file formats. Therefore, the data needs to be harmonized, that means placed into similar formats before comparisons can be made.\n",
-    "* The coordinate reference systems used to locate measurements have changed over the years, as the Earth's surface is not static and changes shape. To account for these changes, terrestrial reference frames that relate latitude and longitude to points on the Earth are updated on a regular basis. Since the launch of ICESat/GLAS, the International Terrestrial Reference Frame [(ITRF)](https://www.iers.org/IERS/EN/DataProducts/ITRF/itrf.html) has been updated three times. The geolocation of a point measured at the beginning of the record and the end of the record is not the same even though the latitude and longitude is the same. These changes in geolocation need to be reconciled to allow meaningful comparisons within the long-term data record.\n",
-    "\n",
-    "The companion [Applying Coordinate Transformations to Facilitate Data Comparison](./corrections) notebook contains information about how to perform ITRF transformations using [PyProj](https://pyproj4.github.io/pyproj/stable/index.html).\n",
-    "\n",
     "### Pre-IceBridge\n",
     "\n",
     "The Airborne Topographic Mapper (ATM) is a conically-scanning laser altimeter that measures the surface topography of a swath of terrain directly beneath the path of an aircraft. ATM surveys can be used to detect surface changes. Differences of laser swaths surveyed over the same area but a few years apart can be used to estimate elevation changes between the first and second survey. Comparing the surveys conducted 1993-4 and 1998-9 resulted in the first comprehensive assessment of the mass balance change of the Greenland ice sheet ([Krabill et al., 1999](https://science.sciencemag.org/content/283/5407/1522), [2000](https://science.sciencemag.org/content/289/5478/428)).  ATM surveys can also be used to calibrate/validate satellite altimeter measurements (e.g. [Martin et al., 2005](https://atm.wff.nasa.gov/files/browser/ATM_Calibration_Procedures_and_Accuracy_Assessment_2012.pdf)).  The ATM was deployed on a wide variety of platforms, including the NASA P3, a Chilean Navy P3, a US Navy P3, the NASA DC8, the NCAR C-130, and a half-dozen Twin Otters to collected high quality topographic data. For a complete list of the ATM deployments visit [https://atm.wff.nasa.gov/deployments/](https://atm.wff.nasa.gov/deployments/)\n",
@@ -90,6 +84,26 @@
     "**Note**: If you have questions about the data sets please refer to the user guides or contact NSIDC user services at [email protected]"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Challenges\n",
+    "\n",
+    "The wealth of data from these missions presents an opportunity to study the evolution of ice thickness over several decades. However, combining data from these missions presents several challenges:\n",
+    "\n",
+    "* Data from the Airborne Topographic Mapper (ATM) flown during the IceBridge campaigns is stored in four different file formats. ICESat/GLAS and ICESat-2 data are also in different file formats. Therefore, the data needs to be harmonized, that means placed into similar formats before comparisons can be made.\n",
+    "* The coordinate reference systems used to locate measurements have changed over the years, as the Earth's surface is not static and changes shape. To account for these changes, terrestrial reference frames that relate latitude and longitude to points on the Earth are updated on a regular basis. Since the launch of ICESat/GLAS, the International Terrestrial Reference Frame [(ITRF)](https://www.iers.org/IERS/EN/DataProducts/ITRF/itrf.html) has been updated three times. The geolocation of a point measured at the beginning of the record and the end of the record is not the same even though the latitude and longitude is the same. These changes in geolocation need to be reconciled to allow meaningful comparisons within the long-term data record.\n",
+    "\n",
+    "The `iceflow` Python library addresses these concerns by providing the ability to search, download, and access laser altimetry data from (pre-)Operation IceBridge and ICESat/GLAS datasets. The library also supports International Terrestrial Reference Frame (ITRF) transformations to facilitate comparisons across datasets.\n",
+    "\n",
+    "Companion Jupyter notebooks give additional information and contain example code about `iceflow`.\n",
+    "\n",
+    "[NSIDC Iceflow example](./iceflow-example) provides an example of how to search for, download, and interact with `ILATM1B v1` data for a small area of interest. This notebook also illustrates how to perform [ITRF](https://itrf.ign.fr/) transformations to facilitate comparisons across datasets. To learn more about ITRF transformations, see the [Applying Coordinate Transformations to Facilitate Data Comparison](./corrections) notebook.\n",
+    "\n",
+    "[Using iceflow with icepyx to Generate an Elevation Timeseries](./iceflow-with-icepyx) shows how to search for, download, and interact with a large amount of data across many datasets supported by `iceflow`. It also illustrates how to utilize [icepyx](https://icepyx.readthedocs.io/en/latest/) to find and access ICESat-2 data. Finally, the notebook provides a simple time-series analysis for elevation change over an area of interest across `iceflow` supported datasets and ICESat-2."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},