Nicholas Hamm

Associate Professor

Geographical Sciences / Faculty of Science and Engineering
Staff Profile Portrait Image



Room 439, Sir Peter Mansfield Building


University of Nottingham Ningbo China


199 Taikang East Road, Ningbo, 315100, China


+86 (0) 574 8818 0000 Extension 8980


BSc (Hons)

MRes (Lond)

PhD (Soton)


Dr Hamm graduated with BSc and MRes degrees from University College London and followed this with a PhD at the University of Southampton.   He has held academic and research appointments at the University of Twente (The Netherlands), University of Southampton (UK) and the University of Bristol (UK). He has also held visiting appointments at the University of Queensland (Australia) and RMIT University (Australia).  

Expertise Summary

Dr Hamm is a geoinformation scientist with specific interests in uncertainty, spatial data quality and the integration of heterogeneous datasets. He also has a background in geography and environmental science. He has particular expertise in geostatistical modelling of spatial and spatial-temporal data and the evaluation of uncertainty in environmental models and geographic data. He works with a range of environmental datasets including those from airborne and spaceborne remote sensing, in situ environmental sensors and environmental models. Applications include environmental monitoring (e.g., air quality, land cover), environmental modelling (e.g., species distribution modelling, biogeochemical cycles) and geo-health (e.g., neglected tropical diseases).   


I teach undergraduate courses relating to geoinformation science, remote sensing and environmental analysis.  I have taught postgraduate courses in spatial data quality, geostatistics and remote sensing.

Research interests

Geoinformation science

Geostatistics and spatial-temporal statistics

Novel geospatial datasets

Earth observation, remote sensingUncertainty in geospatial data and analysis


For further details see Google Scholar and Orcid.

Refereed Journal Papers (ISI)

Cadavid Restrepo, A. M., Y. R. Yang, D. P. McManus, D. J. Gray, T. S. Barnes, G. M. Williams, R. J. Soares Magalhães, N. A. S. Hamm and A. C. A. Clements (2018). Spatiotemporal patterns and environmental drivers of human echinococcoses over a twenty-year period in Ningxia Hui Autonomous Region, China, Parasites & Vectors, 11, 108.  doi: 10.1186/s13071-018-2693-z

Chen, G., L. D. Knibbs, W. Zhang, S. Li, W. Cao, J. Guo, H. Ren, B. Wang, H. Wang, G. M. Williams, N. A. S. Hamm, and Y. Guo. (2018) Estimating spatial and temporal PM1 concentrations in China with satellite remote sensing, meteorology, and land use information, Environmental Pollution, 233, 1086-1094. doi: 10.1016/j.envpol.2017.10.011

Raj, R., C. van der Tol, N. A. S. Hamm and A. Stein (2018) Bayesian Integration of Flux Tower Data into Process-Based Simulator for Quantifying Uncertainty in Simulated Output, Geoscientific Model Development Discussions, 11, 83-101.  doi: 10.5194/gmd-11-83-2018

Mukherjee, S., Srivastav, S.K., Gupta, P.K., Hamm, N.A.S. and Tolpekin, V.A. (2017) An Algorithm for Inter-calibration of Time-Series DMSP/OLS Night-Time Light Images. Proceedings of the National Academy of Sciences, India Section A: Physical Sciences, 87 (4): 7210. doi: 10.1007/s40010-017-0444-8

Cadavid Restrepo, A. M., Y. R. Yang, N. A. S. Hamm, D. J. Gray, T. S. Barnes, G. M. Williams, R. J. Soares Magalhães, D. P.McManus, D. Guo & A. C. A. Clements (2017) Land cover change during a period of extensive landscape restoration in Ningxia Hui Autonomous Region, China (1980-2015), Science of the Total Environment, 598, 669-679.  doi: 10.1016/j.scitotenv.2017.04.124

Araujo Navas, A. L., N. A. S. Hamm, R. J. Soares Magalhães & A. Stein (2016) Mapping Soil Transmitted Helminths and Schistosomiasis under Uncertainty: Systematic Review and Critical Appraisal of Evidence, PLoS Neglected Tropical Diseases, 10(12), e0005208.  doi: 10.1371/journal.pntd.0005208

Datta, A., S. Banerjee, A. O. Finley, N. A. S. Hamm and M. Schaap (2016). Nonseparable dynamic nearest neighbor Gaussian process models for large spatio-temporal data with an application to particulate matter analysis. The Annals of Applied Statistics 10(3): 1286-1316. doi: 10.1214/16-AOAS931

Raj, R., N. A. S. Hamm, C. van der Tol and A. Stein (2016). Uncertainty analysis of gross primary production partitioned from net ecosystem exchange measurements. Biogeosciences 13: 1409–1422. doi: 10.5194/bg-13-1409-2016

Cadavid Restrepo, A. M., Y. R. Yang, D. P. McManus, D. J. Gray, P. Giraudoux, T. S. Barnes, G. M. Williams, R. J. Soares Magalhães, N. A. S. Hamm and A. C. A. Clements (2016). The landscape epidemiology of echinococcoses. Infectious Diseases of Poverty 5: 13. doi: 10.1186/s40249-016-0109-x

Hamm, N. A. S., A. O. Finley, M. Schaap and A. Stein (2015). A spatially varying coefficient model for mapping air quality at the European scale. Atmospheric Environment 102: 393-405. doi: 10.1016/j.atmosenv.2014.11.043 

Hamm, N. A. S., R. J. Soares Magalhães and A. C. A. Clements (2015). Earth Observation, Spatial Data Quality and Neglected Tropical Disesases. PLoS Neglected Tropical Diseases 9(12): e0004164. doi: 10.1371/journal.pntd.0004164

Naimi, B., N. A. S. Hamm, T. A. Groen, A. K. Skidmore and A. G. Toxopeus (2014). Where is positional uncertainty a problem for species distribution modelling? Ecography 37(2): 191-203. doi: 10.1111/j.1600-0587.2013.00205.x

Raj, R., N. A. S. Hamm, C. van der Tol and A. Stein (2014). Variance-based sensitivity analysis of BIOME-BGC for gross and net primary production. Ecological Modelling 292: 26-36. doi: 10.1016/j.ecolmodel.2014.08.012

Odongo, V. O., N. A. S. Hamm and E. J. Milton (2014). Spatio-Temporal Assessment of Tuz Gölü, Turkey as a Potential Radiometric Vicarious Calibration Site. Remote Sensing 6(3): 2494-2513. doi: 10.3390/rs6032494

Raj, R., N. A. S. Hamm and Y. Kant (2013). Analysing the effect of different aggregation approaches on remotely sensed data. International Journal of Remote Sensing 34(14): 4900-4916. doi: 10.1080/01431161.2013.781289

Yaseen, M., N. A. S. Hamm, V. Tolpekin and A. Stein (2013). Anisotropic kriging to derive missing coseismic displacement values obtained from synthetic aperture radar images. Journal of Applied Remote Sensing 7. doi: 10.1117/1.jrs.7.073580

Zurita-Milla, R., J. A. E. van Gijsel, N. A. S. Hamm, P. W. M. Augustijn and A. Vrieling (2013). Exploring Spatiotemporal Phenological Patterns and Trajectories Using Self-Organizing Maps. IEEE Transactions on Geoscience and Remote Sensing 51(4): 1914-1921. doi: 10.1109/tgrs.2012.2223218

Yaseen, M., N. A. S. Hamm, T. Woldai, V. A. Tolpekin and A. Stein (2013). Local interpolation of coseismic displacements measured by InSAR. International Journal of Applied Earth Observation and Geoinformation 23: 1-17. doi: 10.1016/j.jag.2012.12.002

Hamm, N. A. S., P. M. Atkinson and E. J. Milton (2012). A per-pixel, non-stationary mixed model for empirical line atmospheric correction in remote sensing. Remote Sensing of Environment 124: 666-678. doi: 10.1016/j.rse.2012.05.033

Zhang, Y., N. A. S. Hamm, N. Meratnia, A. Stein, M. van de Voort and P. J. M. Havinga (2012). Statistics-based outlier detection for wireless sensor networks. International Journal of Geographical Information Science 26(8): 1373-1392. doi: 10.1080/13658816.2012.654493

Naimi, B., A. K. Skidmore, T. A. Groen and N. A. S. Hamm (2011). Spatial autocorrelation in predictors reduces the impact of positional uncertainty in occurrence data on species distribution modelling. Journal of Biogeography 38(8): 1497-1509. doi: 10.1111/j.1365-2699.2011.02523.x

Jeganathan, C., N. A. S. Hamm, S. Mukherjee, P. M. Atkinson, P. L. N. Raju and V. K. Dadhwal (2011). Evaluating a thermal image sharpening model over a mixed agricultural landscape in India. International Journal of Applied Earth Observation and Geoinformation 13(2): 178-191. doi: 10.1016/j.jag.2010.11.001

Stein, A., N. A. S. Hamm and Q. Ye (2009). Handling uncertainties in image mining for remote sensing studies. International Journal of Remote Sensing 30(20): 5365-5382. doi: 10.1080/01431160903130895

Hamm, N. A. S., J. W. Hall and M. G. Anderson (2006). Variance-based sensitivity analysis of the probability of hydrologically induced slope instability. Computers & Geosciences 32(6): 803-817. doi: 10.1016/j.cageo.2005.10.007

Al-Khudhairy, D. H. A., J. R. Thompson, H. Gavin and N. A. S. Hamm (1999). Hydrological modelling of a drained grazing marsh under agricultural land use and the simulation of restoration management scenarios. Hydrological Sciences Journal-Journal Des Sciences Hydrologiques 44(6): 943-971. doi: 10.1080/02626669909492291

Book Chapters

Hamm, N. A. S., M. van Lochem, G. Hoek, R. Otjes, S. van der Sterren & H. Verhoeven (2016) The Invisible Made Visible: Science and Technology." In Aireas: Sustainocracy for a Healthy City: The Invisible Made Visible Phase 1, edited by Jean-Paul Close, 51-77, Dordrecht, Springer. DOI: 10.1007/978-3-319-26940-5_3. 

Hamm, N., P. M. Atkinson & E. J. Milton. 2004. On the effect of positional uncertainty in field measurements on the atmospheric correction of remotely sensed imagery. In X. Sanchez Vila, J. Carrera & J. J. Gomez Hernandez(eds.) GeoEnv IV - Geostatistics for Environmental Applications, Kluwer Academic Publishers, Dordrecht, 91-102.