Dr Feng Mao BSc, MRes, MPhil, PhD, FRGS

Dr Feng Mao

School of Geography, Earth and Environmental Sciences
Research Fellow

Contact details

Address
School of Geography, Earth and Environmental Sciences
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Feng’s main research interest is in the intersection of environmental science, technology and policy. His research mainly addresses three themes: (1) hydroecology and ecosystem services, (2) evidence-based environmental policies and adaptive management, and (3) environmental data collection via sensor networks, data analysis and visualisation.

Qualifications

  • PhD in Geography, University of Cambridge
  • MPhil in Politics, University of Cambridge
  • MRes in Biodiversity and Conservation, University of Leeds
  • BSc in Natural Sciences and Biology, Zhejiang University

Biography

Feng is currently working as a Research Fellow on the ESPA-funded “Mountain EVO” project, which aims to alleviate poverty in remote mountain areas by developing environmental virtual observatories and promoting adaptive governance of ecosystem services.

Feng did his PhD in the Department of Geography, University of Cambridge. His PhD research focused on the science-policy interface in the area of hydroecology and integrated river basin management in the European Union and China. He investigated how the existing integrated river basin management methods could be supported by scientific evidence, quantitative methods and visualisation tools, and how scientific evidence as a source of knowledge was balanced by subjective management considerations.

Feng holds a BSc in Natural Sciences and Biology from the Zhejiang University, an MRes in Biodiversity and Conservation from the University of Leeds, and an MPhil in Politics from the University of Cambridge. He intended to do research on environmental issues with both natural and social science understanding.

Other activities

Fellow, Royal Geographical Society

Publications

Mao, F. and Richards, K.S. (2012) Irreversible river water quality and the concept of the reference condition. Area, 44: 423–431.

Mao, F., Shi, Y. and Richards, K.S. (2014) rivervis: River Visualisation Tool. An R package on CRAN. URL http://cran.r-project.org/package=rivervis.

View all publications in research portal