As icesat-2 moves closer to its projected launch date of september 12, 2018, the.RE remains a significant amount of work required on the development of the land/vegetation gridded products (atll 8) as…

This $148,038.31 federal grant was awarded by the National Aeronautics and Space Administration (NASA) Shared Services Center to the University of Texas at Austin (UT Austin) Applied Research Laboratories (ARL) Division. The purpose of the grant is to develop a methodology for producing a gridded global terrain and canopy height product from the data collected by the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission. The objectives include analyzing and visualizing the ICESat-2 data across a 1-kilometer global grid, determining the best gridding approach, and characterizing the uncertainty of the final gridded products. This work will support the development of the ICESat-2 Land/Vegetation Gridded Products (ATL18) and is intended to benefit land surface models and global climate models. The grant does not have a set-aside designation and runs through April 3, 2021. UT Austin ARL is a subsidiary of the University of Texas System and has a long history of providing research, development, testing, and evaluation services to federal agencies like the Department of Defense and NASA.

As icesat-2 moves closer to its projected launch date of september 12, 2018, the.RE remains a significant amount of work required on the development of the land/vegetation gridded products (atll 8) as the focus to this point has been directed toward the development of the icesat-2 along-track land/vegetation gridded products (a TL08). The desire of the TE1TESTRIAL science community is to have accurate global products of terrain heights, canopy heights, and canopy cover at a moderate spatial resolution (LKM or better). The purpose of this ptoject is to investigate the best methodology for producing a gridded giobal teitain and canopy height product from the ATL08 along-track data product. The ATL08 product from the icesat-2 mission will report estimates of terrain and canopy height at 100 M increments along the orbit path. Although icesat- 2S gridded products may not be at the spatial resolution desired for some local studies, atli 8 will provide key data products regarding vegetation structure and topography at a resolution that will be of great importance-particularly for land surface models and global climate models. Temporal resolution: IT is anticipated that 3 years oftcesat-2 measurements will be required to produce a global I KM product such that sufficient sampling exists in each cell (i.e. icesat-2 data in 80 percent of the global 1 KM cells). Although the tirne required to produce an atli 8 gridded product with sufficient sampling will require multiple years, we would like to produce a gridded product on an annual basis. IT is envisioned that first version(S) of the a TL 18 gridded product will maintain the 1 KM resolution but contain a large amount of unpopulated cells. As more data is collected from icesat-2, the a TLL 8 will continue to evolve and improve as more cells are populated. Objectives there are four objectives proposed for this research. The first two deal specifically with analytics and visualization of a global L KM grid. Specifically, we and the PSO will need to know where ICESAT2 data has been successfully collected throughout the duration of the mission. The final two objectives are focused on the gridding methodology and how to characterize the errors associated with the data at a 1 KM scale. Specifically, the objectives are as follows: 1) develop a method to generate KML files for valid a TL08 products indicating where successful ATL08 data have been acquired versus data obscured by cloud cover. This INFO1MATION will help the project science office (PSO) to DETE11NINE the prioritization of pointing and impact of off-pointing to to OS (targets of OPP01TUNITY). These KM! Files will not only provide a visual representation of successful acquisition of ATL08 data but will also provide critical weighting parameters for creation of the gridded product. 2) compute the monthly cloud statistics for a global L KM grid using cloudsat/calipso data. The desire to have monthly gridded cloud data will help inform the prioritization of pointing and impact of off-pointing to toos (targets of opportunity). 3) determine the best gridding methodology (e.g. averaging, weighted average) for the ATL08 data based on the spatial distribution of ground-tracks. 4) characterize the uncertainty of the a TL18 gridded products based on the uncertainty values reported on the ATL08 data product as well as the impact of the gridding methodology.