We aim at improving understanding and prediction of geographical systems by innovating methods and tools. Our research is at the intersection of three domains (see below).
Methods & Software Development
We design methods and implement software for simulation of large, heterogeneous geographical systems:
Representation of fields and agents in simulation models to enable heterogeneous system modelling
Simulation on supercomputers to run models with big data
Model data integration techniques to constrains models to observations
Development of algorithms and modelling framework for hardware-scalable tools and applications to geographical data-analysis. In this project, Kor de Jong develops a new generation of modelling tools that enable parallel executation of models on supercomputers. We closely cooperate with Prof Dr M. van Kreveld, Dr D. Panja (Dep. of Information and Computing Sciences).
The LUE physical data model for heterogeneous data. Enables storage of heterogeneous spatio-temporal data, that is both continuous fields and discrete, mobile, agents. We are currently working on the development software that will enable reading and writing data to the data model and for manipulation of the data stored.
de Bakker, M. P., de Jong, K., Schmitz, O., & Karssenberg, D. (2017). Design and demonstration of a data model to integrate agent-based and field-based modelling. Environmental Modelling & Software, 89, 172-189.
Karssenberg, D., Schmitz, O., Salamon, P., de Jong, K., & Bierkens, M. F. P. (2010). A software framework for construction of process-based stochastic spatio-temporal models and data assimilation. Environmental Modelling & Software, 25(4), 489-502.
Complexity Science and Data Science
Due to their intermediate number of interacting system components, most geographical systems show distinct mechanisms, such as self-organisation and critical shifts, that categorizes them as complex systems. It is essential to understand these mechanisms because they are central to system behaviour and thus essential to prediction. Our team explores complex geographical systems by simulation modelling and through statistical and machine learning techniques on large geographical data sets.
Taking a remote look at canopy nitrogen to improve global climate models. PhD project of Yasmina Loozen. With Prof Dr S.M. de Jong, Prof Dr M.J. Wassen, and Dr K.T. Rebel.
Verstegen, J. A., Karssenberg, D., van der Hilst, F., & Faaij, A. P. C. (2016). Detecting systemic change in a land use system by Bayesian data assimilation Environmental Modelling & Software, 75, 424–438.
Vannametee, E., Babel, L. V, Hendriks, M. R., Schuur, J., de Jong, S. M., Bierkens, M. F. P., & Karssenberg, D. (2014). Semi-automated mapping of landforms using multiple point geostatistics. Geomorphology, 221, 298–319.
We use complexity science and data science methods and tools to advance our understanding of geographical systems, with a particular focus on human-environment interactions and global scale assessment.
One of our research foci is the external exposome (wiki) which encompasses all human exposures to the the environment. It is known to be an important determinant of health and disease. As direct measurement of the external exposome is mostly not feasible, research in exposome-health relations needs to rely on estimations of external exposures through modelling. This requires quantification of the environmental variables (e.g. air pollution, green space) as well as human space-time activity trajectories within this environment. We cooperate with health researchers, epidemiologists, and risk assessment researchers in a number of projects. Our role is the innovation of external exposome modelling.
In addition we use spatial simulation models for land use change, ecosystem services, (global) hydrology, geomorphology and related processes.
Current projects include:
The Global Geo Health Data Center creates data sets and software for assessment of human exposures to our environment, for instance air pollution, urban food landscape, or green space. Our team cooperates with epidemiologists and risk assessment scientists to improve our understanding of the role of the external Exposome in human health and disease.
Exposome NL. Gravitation programme funded by the Dutch Science Foundation. Multiple partners, 2020-2028.
Impact of personal environmental exposure on health. PhD project of Anna-Maria Ntarladima. With Prof Dr Rick Grobbee and Dr Ilonca Vaartjes.
Sutanudjaja, E. H., van Beek, R., Wanders, N., Wada, Y., Bosmans, J. H. C., Drost, N., van der Ent, R. J., de Graaf, I. E. M., Hoch, J. M., de Jong, K., Karssenberg, D., López López, P., Peßenteiner, S., Schmitz, O., Straatsma, M. W., Vannametee, E., Wisser, D., & Bierkens, M. F. P. (2018). PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model. Geoscientific Model Development, 11(6), 2429–2453.
Verstegen, J. A., van der Hilst, F., Woltjer, G., Karssenberg, D., de Jong, S. M., & Faaij, A. P. C. (2016). What can and can’t we say about indirect land-use change in Brazil using an integrated economic - land-use change model? GCB Bioenergy, 8(3), 561–578.
Sociology of Environmental Model Construction
Current projects include:
Mediating models: implications on scientific research and communication, PhD project of Lucie Babel. With Dominique Vinck (Institut des Sciences Sociales, Faculty of Social and Political Sciences, University of Lausanne, Switzerland) and Prof Dr M.F.P. Bierkens (Dep. of Physical Geography, Utrecht Univ.).