Professor Mark Danson

Professor in Geography

  • Peel Building Room 305
  • T: +44 (0)161 295 4038
  • E: f.m.danson@salford.ac.uk
  • SEEK: Research profile

Biography

I am Professor of Environmental Remote Sensing and joined the University in 1990. I have a first degree and PhD in Geography from the University of Sheffield and previously held academic positions at the Universities of Sheffield and Nottingham. I was promoted to Professor in 2000 and from 2004-2008 I was Associate Dean (Research) in the Faculty of Science, Engineering and Environment.

I am a recent past editor of the International Journal of Remote Sensing, and past member of the Natural Environment Research Council Peer Review College. From 2005-2009 I was UK Representative for EU COST Action 734, Climate Change and Variability Impacts of European Agriculture and in 2013-14 I was a Royal Society Leverhulme Trust Senior Research Fellow. Since my appointment at Salford I have published more than 70 peer-reviewed journal papers, held research grants worth in excess of £2 million and successfully supervised 15 PhD candidates.

Teaching

I teach on undergraduate modules in Earth Surface Processes, Environmental Remote Sensing, and Research Skills, and at postgraduate level I contribute to the UniGIS Distance Learning MSc in Geographical Information Systems. 

Research Interests

My main research interests are concerned with mapping, modelling and understanding environmental change, specifically the effects of climate and human activity on the biosphere. My main area of expertise is in the application of Earth Observation satellite and airborne remote sensing imagery to monitor change in ecosystems. I have pioneered the use of remote sensing to measure vegetation water content and applied these methods in research to predict wildfires in the Mediterranean and UK.

I have also used remote sensing to map landscape in China and central Asia and model the transmission of the deadly parasite Echinococcus multilocularis. Most recently I have developed the World’s first dual-channel full-waveform terrestrial laser scanner that is now being used to make the most accurate three-dimensional structural measurements of vegetation canopies ever made.

Qualifications and Memberships

BSc (Hons) Geography (First Class), University of Sheffield, 1984

PhD Environmental Remote Sensing, University of Sheffield, 1989

Member of the Remote Sensing and Photogrammetry Society

Publications

Hancock, S., Gaulton, R. and Danson, F.M., 2017, Angular reflectance of leaves with a dual-wavelength terrestrial lidar and its implications for leaf-bark separation and leaf moisture estimation. IEEE Transactions on Geoscience and Remote Sensing, 55, 3084 – 3090.

Schofield, L.A., Danson, F.M., Entwistle, N.S., Gaulton, R. and Hancock, S., 2016. Radiometric calibration of a dual-wavelength terrestrial laser scanner using neural networks. Remote Sensing Letters, 7(4): 299-308.

Marston, C.G., Giraudoux, P., Armitage, R.P., Danson, F.M., Reynolds, S.C., Wang, Q., Qui, J., Craig, P.S., 2016. Vegetation phenology and habitat discrimination: Impacts for E. multilocularis transmission host modelling. Remote Sensing of Environment, 176: 320-327.

Newnham, G.J., Armston, J.D., Calders, K., Disney, M.I., Lovell, J.L., Schaaf, C.B, Strahler, A.H., Danson, F.M., 2015, Terrestrial laser scanning for plot-scale forest measurement. Current Forestry Reports, 1, 239-251. Open Access

Hancock, S., Armston, J., Li, Z., Gaulton, R., Lewis, P., Disney, M., Danson, F.M., Strahler, A.H. Schaaf, C.B., Anderson, K., Gaston, K.J., 2015. Waveform lidar over vegetation: An evaluation of inversion methods for estimating return energy. Remote Sensing of Environment, 164: 208-224.

Danson, F.M., Gaulton, R., Armitage, R.P., Disney, M.I., Gunawan, O., Lewis, P., Pearson, G., Ramirez, A.F., 2014. Developing a dual-wavelength full-waveform terrestrial laser scanner to characterize forest canopy structure. Agricultural and Forest Meteorology, 198: 7-14. Open Access

Gaulton, R., Danson, F.M., Ramirez, F. A., Gunawan, O. (2013) The potential of dual-wavelength laser scanning for estimating vegetation moisture content. Remote Sensing of Environment, 132, 32-39.

Armitage, R.P., Ramirez, F.A., Danson, F.M., & Ogunbadewa, E.Y. (2013) Probability of cloud-free observation conditions across Great Britain estimated using MODIS cloud mask, Remote Sensing Letters, 4, 427-435.

Al-Moustafa, T., Armitage, R.P., Danson, F.M. (2012) Mapping fuel moisture content in upland vegetation using airborne hyperspectral imagery. Remote Sensing of Environment, 127, 74-83.

Garcia, M., Riano, D., Chuvieco, E., Salas, J., & Danson, F.M. (2011). Multispectral and LiDAR data fusion for fuel type mapping using Support Vector Machine and decision rules. Remote Sensing of Environment, 115, 1369-1379.

Garcia, M., Danson, F.M., Riano, D., Chuvieco, E., Ramirez, F.A., & Bandugula, V. (2011). Terrestrial laser scanning to estimate plot-level forest canopy fuel properties. International Journal of Applied Earth Observation and Geoinformation, 13, 636-645.

Garcia, M., Riano, D., Chuvieco, E., & Danson, F.M. (2010). Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data. Remote Sensing of Environment, 114, 816-830.