Professor Mark Danson

Professor Mark Danson

Unit Tutor
University of Salford

Contact Details:

Tel: +44 (0) 161 295 4038
Fax: +44 (0) 161 295 5015

Professor Mark Danson is Professor of Environmental Remote Sensing, University of Salford.


His research interests are in mapping, modelling and understanding environmental change, specifically the effects of climate change and human activity on the biosphere. His focus is on the application of Earth Observation satellite data, airborne remote sensing imagery, and ground-based instruments, to monitor change in forest ecosystems. He recently developed one of world’s first dual-channel full-waveform terrestrial laser scanner that is now being used to record some of the most accurate three-dimensional structural measurements of vegetation canopies ever made. Professor Danson was a Royal Society Leverhulme Trust Senior Research Fellow 2013-14.




Selected 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 (in press).


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.


Bachtiar, V.S., Davies, F. and Danson, F.M., 2014. A combined model for improving estimation of atmospheric boundary layer height. Atmospheric Environment, 98: 461-473.


Ogunbadewa, E.Y., Armitage, R.P. and Danson, F.M., 2014. Optical medium spatial resolution satellite constellation data for monitoring woodlands in the UK. Forests, 5(7): 1798-1814.


Marston, C.G., Danson, F.M., Armitage, R.P., Giraudoux, P., Pleydell, D.R.J., Wang, Q., Qui, J., Craig, P.S., 2014. A random forest approach for predicting the presence of Echinococcus multilocularis intermediate host Ochotona spp. presence in relation to landscape characteristics in western China. Applied Geography, 55: 176-183.


Gaulton, R., Danson, F.M., Ramirez, F.A. and 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. and Ogunbadewa, E.Y., 2013. Probability of cloud-free observation conditions across Great Britain estimated using MODIS cloud mask. Remote Sensing Letters, 4(5): 427-435.


Yebra, M., Chuvieco, E., Jurdao, S., Danson, F.M., Dennison, P., Hunt, E.R., Qi, Y., Riano, D., Zylstraet, P., 2013. A global review of remote sensing of live fuel moisture content for fire danger assessment: Moving towards operational products. Remote Sensing of Environment, 136: 455-468.


Danson, F.M., Morsdorf, F, Koetz, B and Allgöwer, B., 2009, Airborne and terrestrial laser scanning for measuring vegetation canopy structure. In G.L. Heritage and A.R.G. Large, UNIGIKS Laser Scanning for the Environmental Sciences, Wiley-Blackwell.


Pleydell, D.R.J., Yang, Y.R., Danson, F.M., Raoul, F., Craig, P.S., McManus, D.P., Vuitton, D.A., Wang, Q. and Giraudoux, P., 2008, Landscape Composition and Spatial Prediction of Alveolar Echinococcosis in Southern Ningxia, China. PLOS Neglected Tropical Diseases, 2 (9), e287.


Danson, F.M., Armitage, R.P. and Marston, CG, 2008, Spatial and temporal modelling for parasite transmission studies and risk assessment. Parasite, 15(3): 463-468.


Danson, F.M., Giraudoux, P., Pleydell, D.R.J., and Craig, P.S et al, 2007, Landscape change, disease transmission and remote sensing in China, Journal of Remote Sensing, 11 (5), 728-731.


Danson, F.M., Hetherington, D., Morsdorf, F., Koetz, B and Allgöwer, B., 2007, Three-dimensional forest structure from terrestrial laser scanning, IEEE Geoscience and Remote Sensing Letters, 4, 157-160.


Chuvieco, E., Riaño, D., Danson, F.M. and Martin, P., 2006, Use of a radiative transfer model to simulate the spectral response to burn severity values. Journal of Geophysical Research – Biogeosciences, 111 (G4), G04S09.


Danson, F.M., Giraudoux, P., and Craig, P.S., 2006, Spatial modelling and ecology of Echinococcus multilocularis transmission in China. Parasitology International, 55, 227-231.


Yang, Y.R., Danson, F.M. and 20 other authors, 2006, Community surveys and risk factor analysis of human alveolar and cystic echinococcosis in Ningxia Hui Autonomous Region, China, Bulletin of The World Health Organization 84, 714-721.


Boyd, D.S. and Danson, F.M., 2005, Satellite remote sensing of forest resources: three decades of research development, Progress in Physical Geography, 29, 1-26.


Graham, A. and Danson, F.M., 2005, Remote sensing and landscape ecology: impacts on modelling disease transmission, Progress in Physical Geography, 29, 77-91.


Danson, F.M., Bowyer, P., Pleydell, D.R.J. and Craig, P.S., 2004, Echinococcus multilocularis: the role of satellite remote sensing, GIS and spatial modelling. South-East Asian Journal of Tropical Medicine and Health, 35, 189-193.


Danson, F.M. and Bowyer, P., 2004, Estimating live fuel moisture content from remotely sensed reflectance, Remote Sensing of Environment, 92, 309-321.