Meet a NFM Researcher: Dr Will Maslanka, University of Reading, working on the Landwise project
Will will be presenting on Improving Soil Moisture Estimation from Space Radar alongside Professor Keith Morrison as part of our webinar series for NFM researchers and practitioners on 15 April 12:30 – 13:30. Find out more and sign up for your free place here.
With a background in physical geography and meteorology which he studied at the University of Reading, Will joined the Landwise team in May 2019. He is a postdoctoral researcher in Remote Sensing.
‘My research for Landwise to date has focused on building a timeseries of relative soil moisture data for the Thames, Loddon and Kennet catchments in south east England using Sentinel 1 satellite observations. This allows us to see seasonal changes, impacts of drought, storms, and even individual storm tracks. It also allows comparison of different land use including land scale NFM measures such as changes to agricultural practice’.
We asked Will about his studies and work on the Landwise project.
‘My PhD research was on how to improve remote sensing of snow packs to improve data for modelling. There wasn’t enough snow in the UK for this work so I spent two dark cold winters in Finland’s Meteorological Institute Arctic Space Centre within the arctic circle! An equation I developed is now used to improve representation of microwave scattering from snow crystals and in turn snow depth, important for water resource planning. ’
‘After finishing my PhD, I worked for the Environment Agency as a flood modeller and forecaster for Hertfordshire, North London and the Thames basin. This was great experience to take into the Landwise project where my research is in many of the same geographical areas. It’s also been useful to have contacts at the EA, as they are one of our main project partners’.
Will is excited that a drone and rig are now available so the next stage in his research can get underway soon.
‘We will be working with the Centre for Ecology and Hydrology (CEH) to compare satellite data with often more precise data collected from ground based and drone radar. I’m looking forward to the field studies and sharing the observations with the modelling team to help them refine predictions of land use change impacts. The work will involve 3D computer imaging of land use in different locations and in preparation I’ve been building a 3D image of the lawn in my back garden to sharpen my understanding of the software!’
‘Our ultimate aim is that the work will lead to the development of tools for land managers, including farmers to help inform land management decisions, not least those around NFM.’
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