Postdoctoral researcher: Snow estimation under a vegetation gradient using SnowEx data
We are searching for an enthusiastic postdoctoral researcher with experience in snow modeling, remote sensing observations and data merging to join us in the Belspo SNOPOST project to advance snow estimation, using data collected during the NASA SnowEx campaign. You will be part of the Department of Earth and Environmental Sciences, Division Soil and Water Management, at the KU Leuven (Belgium), leading research on snow remote sensing and modeling. Activities include close collaboration with scientists at NASA Goddard Space Flight Center. Remote sensing of snow water equivalents has been notoriously difficult, especially in forested areas. NASA has launched a multi-year airborne campaign, SnowEx, to collect a wealth of data over a variety of snow covered regions. The first campaign was held in February 2017 in Grand Mesa, Colorado (US), a flat region with varying forest densities. Airborne remote sensing data were collected using multiple traditional and experimental techniques, including lidar, active microwave, and multi/hyper-spectral visible/infrared imagers. In addition, a variety of terrestrial remote sensing data were collected. During the same period, large groups of scientists intensively sampled snow “on the ground”, and satellite missions looked at Grand Mesa “from space”. Finally, snow can also be simulated over this area using land surface models. The SNOPOST project will optimally combine data from this unique dataset, and collaborate with the SnowEx team, to unlock the potential of remote sensing for snow estimation.
- Perform and disseminate high quality research related to snow remote sensing, land surface modeling, and data merging
- Supervise PhD and/or master thesis students
This job comes from a partnership with Science Magazine and