Geospatial Systems - Samuel Christelow
In partnership with
Nottingham Geospatial Institute, University of Nottingham, NG7 2TU
About Samuel Christelow
Hi! I am Sam and I joined Cohort 2 of the Geospatial Systems CDT in September 2020.
I graduated from the University of Nottingham with an MSci (Hons) in Physics in August 2020, with a focus on computational Physics. I have carried this forward into my current research interests in utilising Machine Learning for improving Essential Climate Variable retrievals.
My PhD revolves around improving existing surface soil moisture estimations by combining GNSS Reflectometry data with other spaceborne sensors as well as ancillary vegetation and topographic data, all based on open source data and methodologies. The overall aim is to create a soil moisture product with the high temporal and spatial resolution required for humanitarian and disaster risk use cases. This data fusion is based on an Artificial Neural Network architecture.
Climate change is one of the most pressing issues facing humanity in the 21st century, improving the monitoring of climate change is therefore critical. The use of satellite data for Earth Observation (EO) has great potential in this field and is already widely used for monitoring Essential Climate Variables (ECVs).
My research focuses on the utilisation of GNSS R data in conjunction with more traditional EO data (SAR etc.) to estimate ECVs more accurately and more frequently. This work builds on the novel field of GNSS R in the build-up to the launch of ESA’s HydroGNSS mission in 2024.