David Benz (2018)
Utilizing AI to achieve societal benefit uplift in England's public forest estate
BA Botany, Miami University (1993); MA GIS, Clark University (2003). My professional background includes agricultural work in Africa and decennial census support. The bulk of my experience is in academic research, using GIS and remote sensing to analyse environmental patterns. For my DPhil project I am investigating the application of artificial intelligence to forestry.
Utilising AI to achieve ecosystem service uplift in England’s public forest estate.
Long, P R, D Benz, A C Martin, P W A Holland, M Macias-Fauria, A W R Seddon, R Hagemann, T K Frost, A C Simpson, D J Power, M A Slaymaker, and K J Willis (2018). LEFT – a web-based tool for the remote measurement and estimation of ecological value across global landscapes. Methods in Ecology and Evolution 9, 571-579, doi:10.1111/2041-210X.12924.
Seddon, A W R, M Macias-Fauria, P R Long, D Benz, and K J Willis (2016). Sensitivity of global terrestrial ecosystems to climate variability. Nature 531(7593), 229-232, doi:10.1038/nature16986.
Thorn, J P R, R Friedman, D Benz, K J Willis, and G Petrokofsky (2016). What evidence exists for the effectiveness of on-farm conservation land management strategies for preserving ecosystem services in developing countries? A systematic map. Environmental Evidence 5(13), doi:10.1186/s13750-016-0064-9.
Macias-Fauria, M, A W R Seddon, D Benz, P R Long, and K Willis (2014). Spatiotemporal patterns of warming. Nature Climate Change 4, 845-846.
Scharlemann, J P W, D Benz, S I Hay, B V Purse, A J Tatem, G R W Wint, and D J Rogers (2008). Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data, PLoS One, 3(1):e1408.