I am interested in quantifying and mapping the provision and benefits of Ecosystem Services (ES), particularly those associated with green and blue spaces in an urban setting. A critical part of achieving this is developing our understanding of the interplay between pressures (e.g. noise, air pollution, Urban Heat Island effect) and contextual factors (e.g. land use / land cover (LULC), demographics, poverty, and health indicators) in determining who benefits, where, when, and by how much. An improved understanding of these relationships will allow us to support sustainable and equitable development through accurate ES assessment and scenario modelling.
I use a variety of tools to obtain, process, and analyse a range of data-types, from remotely sensed multi-spectral satellite images to census and socio-economic indicator data. I enjoy developing new methods and modelling techniques in R statistical programming language, but also use other tools and platforms, such as Google Earth Engine and Python.
I am interested in quantifying and mapping the provision and benefits of Ecosystem Services (ES), particularly those associated with green and blue spaces in an urban setting. A critical part of achieving this is developing our understanding of the interplay between pressures (e.g. noise, air pollution, Urban Heat Island effect) and contextual factors (e.g. land use / land cover (LULC), demographics, poverty, and health indicators) in determining who benefits, where, when, and by how much. An improved understanding of these relationships will allow us to support sustainable and equitable development through accurate ES assessment and scenario modelling.
I use a variety of tools to obtain, process, and analyse a range of data-types, from remotely sensed multi-spectral satellite images to census and socio-economic indicator data. I enjoy developing new methods and modelling techniques in R statistical programming language, but also use other tools and platforms, such as Google Earth Engine and Python.