Hagen-Zanker A (2008) A multi-scale metric of compactness of urban change illustrated to 22 European countries., pp. 1-18 University of Liverpool
Hagen-Zanker A (2008) Sensititivity analysis of a cellular automata land use model through multiple metrics of goodness-of-fit, pp. 1-15 Eindhoven University of Technology, Department of Architecture,Building, and Planning
This paper introduces a methodological framework for performance assessment of spatial dynamic models by means of map comparison. The objective is to discern to what extent model performance, expressed by a variety of metrics, can be attributed to endogenously modeled processes or to exogenous model inputs. For this purpose, neutral models of landscape change are introduced that are subject to the same boundary conditions and constraints as the probed model, but otherwise are random except for a reluctance to change. The neutral models serve as benchmark and the difference in performance with the model under investigation can be attributed to the endogenous qualities of the model. Furthermore, the framework makes performance measures over multiple criteria and scales mutually comparable, thus providing insight in strengths and weaknesses of the model. The framework is applied for the performance assessment of a Constrained Cellular Automata land use model for La Réunion (Fr.). Map comparison metrics of land use presence and structure are evaluated at multiple scales. For criteria of land use presence the land use model outperforms the neutral models only at coarse scales, but for criteria of land use structure it performs better on all scales. © 2008 Elsevier B.V. All rights reserved.
Hagen-Zanker A (2007) Quantification and classification of urban change patterns, In: Demaar U (eds.), Proceedings of the 9th International Conference on Geocomputation pp. 1-3 National University of Ireland
Hagen A (2003) Map comparison for the calibration of spatial models, pp. 67-68 Faculty of Geographical Sciences, Utrecht University
Geosimulation is a form of microsimulation that seeks to understand geographical patterns and dynamics as the outcome of micro level geographical processes. Geosimulation has been applied to understand such diverse systems as lake ecology, traffic congestion and urban growth. A crucial task common to these applications is to express the agreement between model and reality and hence the confidence one can have in the model results. Such evaluation requires a geospatial perspective; it is not sufficient if the micro-level interactions are realistic. Importantly the interactions should be such that the meso and macro level patterns that emerge from the model are realistic. In recent years, a host of map comparison methods have been developed that address different aspects of the agreement between model and reality. This paper places such methods in a framework to systematically assess the breadth and width of model performance. The framework expresses agreement at the continuum of spatial scales ranging from local to the whole landscape and separately addresses agreement in structure and presence. A common reference level makes different performance metrics mutually comparable and guides the interpretation of results. The framework is applied for the evaluation of a constrained cellular automata model of the Netherlands. The case demonstrates that a performance assessment lacking either a multi-criteria and multi-scale perspective or a reference level would result in an unbalanced account and ultimately false conclusions.
Hagen-Zanker A, Engelen G, Hurkens J, Vanhout R, Uljee I (2006) Map Comparison Kit 3: User Manual, Research Institute for Knowledge Systems
Hagen-Zanker A (2006) Evaluating the morphological quality of land use models,
Hagen-Zanker A (2005) Neighbourhood based map comparison,
Wickramasuriya RC, Bregt AK, van Delden H, Hagen-Zanker A (2009) The dynamics of shifting cultivation captured in an extended Constrained Cellular Automata land use model, Ecological Modelling 220 pp. 2302-2309
This paper presents an extension to the Constrained Cellular Automata (CCA) land use model of White et al. [White, R., Engelen, G., Uljee, L, 1997. The use of constrained cellular automata for high-resolution modelling of urban land-use dynamics. Environment and Planning B: Planning and Design 24(3), 323-343] to make it better suited for modelling the dynamics of shifting cultivation. In the extended model the time passed since the last land use transition of a location is a factor of its land use potential. The model can now account for the gradual decrease in soil fertility after an area of forest has been cleared for cultivation and also capture the process of regeneration once the plot is fallowed. The model is applied for the Ruhunupura area of Sri Lanka where chena, a particular practice of shifting cultivation, is a common land use that dominates the landscape dynamics. The model is calibrated for the period 1985-2001 and the results are assessed in terms of location to location overlap as well as structural similarity at multiple scales. These results give confidence in the representation of land use dynamics for the main land use classes. On the basis of a long term scenario run for the period 2001-2030, it is verified that the model captures stylized facts related to chena dynamics, in particular shortening fallow periods and increasingly long cultivation periods of chena, as a result of increasing land use pressure. We conclude that the model extension is crucial for regions with substantial areas of shifting cultivation. The extension affects not only the land use class shifting cultivation, but also through spatio-temporal interactions that are already present in the original CCA model the whole land use system is better represented. (C) 2009 Elsevier B.V. All rights reserved.
Hagen-Zanker AH (2009) New ways of supporting decision making: linking qualitative storylines with quantitative modelling, In: Geertman S, Stillwell JCH (eds.), Planning Support Systems Best Practice and New Methods 95 pp. 347-367 Springer
To explore how people will live and work in Europe, what the landscape will look like and what the environmental consequences will be in some 35 years from now, the PRELUDE project (EEA 2007) of the European Environment Agency developed five different land-use scenarios for Europe. The project was carried out according to a Story And Simulation (SAS) approach in which, iteratively, storylines developed in participatory sessions are underpinned by land-use models. Storylines in this context are defined as narratives about future developments in Europe. They provide qualitative information on a broad range of issues in an integrated context.
Hagen-Zanker A, Martens P (2008) Map comparison methods for comprehensive assessment of geosimulation models, 5072 pp. 194-209 Springer
Hagen-Zanker A (2007) A state-space representation for measuring urban change, In: Bunce RGH, Jongman RHG, L.Hojas, Weel S (eds.), 7th IALE World Congress pp. 870-871 IALE
Hagen-Zanker A, Jin Y (2011) Improving geographic scalability of traffic assignment through adaptive zoning.,
van Vliet J, Bregt AK, Hagen-Zanker A (2011) Revisiting Kappa to account for change in the accuracy assessment of land-use change models, Ecological Modelling 222 pp. 1367-1375
Land-use change models are typically calibrated to reproduce known historic changes. Calibration results can then be assessed by comparing two datasets: the simulated land-use map and the actual land-use map at the same time. A common method for this is the Kappa statistic, which expresses the agreement between two categorical datasets corrected for the expected agreement. This expected agreement is based on a stochastic model of random allocation given the distribution of class sizes. However, when a model starts from an initial land-use map and makes changes to it, that stochastic model does not pose a meaningful reference level. This paper introduces K-Simulation, a statistic that is identical in form to the Kappa statistic but instead applies a more appropriate stochastic model of random allocation of class transitions relative to the initial map. The new method is illustrated on a simple example and then the results of the Kappa statistic and K-Simulation are compared using the results of a land-use model. It is found that only K-Simulation truly tests models in their capacity to explain land-use changes over time, and unlike Kappa it does not inflate results for simulations where little change takes place over time. (C) 2011 Elsevier BM. All rights reserved.
Hagen-Zanker A (2006) Comparing continuous valued raster data: a cross disciplinary literature scan, Research Institute for Knowledge Systems (RIKS)
Hagen-Zanker A, de Vries I, Hartholt H (2007) The dilemma of dykes ? Risk and opportunities in a geomorphological simulation at mega timescales, pp. 1-4 TUDelft
Hagen-Zanker A (2006) Map Comparison Kit: Beta extension for continuous valued data, Research Institute for Knowledge Systems (RIKS)
Hagen-Zanker AH, Jin Y (2013) Adaptive zoning for transport mode choice modeling, Transactions in Geographic Information Systems (GIS)
The Fuzzy Kappa statistic expresses the agreement between two categorical raster maps. The statistic goes beyond cell-by-cell comparison and gives partial credit to cells based on the categories found in the neighborhood. When matching categories are found at shorter distances the agreement is higher. Like the well-established Kappa statistic the Fuzzy Kappa statistic expresses the mean agreement relative to the expected agreement. The model underlying the expected agreement assumes absence of spatial autocorrelation in both compared maps. In reality however, spatial autocorrelation does lower the expected agreement as matching categories become less likely to be found close-by. Since most maps have some degree of spatial autocorrelation, the calculated expected agreement is generally higher than the true expected agreement. This leads to counterintuitive results when maps that appear to have considerable agreement obtain negative Fuzzy Kappa values. Furthermore, the Fuzzy Kappa may be biased, as it systematically attributes lower agreement to maps with stronger spatial autocorrelation. This paper proposes an improved Fuzzy Kappa statistic that is based on the same local agreement and has the same attractive properties as the original Fuzzy Kappa. The novelty is that the new statistic accounts for spatial autocorrelation, such that the expected Fuzzy Kappa for maps that are not cross-correlated is equal to zero. The improved statistic is applied on two cases to demonstrate its properties.
Hagen-Zanker A, Jin Y (2010) Adaptive zoning and its effectiveness in spatial economic activity simulation,
Hagen A (2002) Comparison of maps containing nominal data, Research Institute for Knowledge Systems (RIKS)
Hagen-Zanker A, Lajoie G (2007) Multi-criteria, multi-scale, and multi-referenced: A methodology for the evaluation of spatial models, pp. 1-2
Hagen-Zanker A, Jin Y (2012) A New Method of Adaptive Zoning for Spatial Interaction Models, Geographical Analysis 44 (4) pp. 281-301
Spatial interaction models commonly use discrete zones to represent locations. The computational requirements of the models normally arise with the square of the number of zones or worse. For computationally intensive models, such as land use-transport interaction models and activity-based models for city regions, this dependency of zone size is a long-standing problem that has not disappeared even with increasing computation speed in PCs-it still forces modelers to compromise on the spatial resolution and extent of model coverage as well as on the rigor and depth of model-based analysis. This article introduces a new type of discrete zone system, with the objective of reducing the time for estimating and applying spatial interaction models while maintaining their accuracy. The premise of the new system is that the appropriate size of destination zones depends on the distance to their origin zone: at short distances, spatial accuracy is important and destination zones must be small; at longer distances, knowing the precise location becomes less important and zones can be larger. The new method defines a specific zone map for every origin zone; each origin zone becomes the focus of its own map, surrounded by small zones nearby and large zones farther away. We present the theoretical formulation of the new method and test it with a model of commuting in England. The results of the new method are equivalent to those of the conventional model, despite reducing the number of zone pairs by 96% and the computation time by 70%. © 2012 The Ohio State University.
van Vliet J, Hagen-Zanker AH, van Delden H, Hurkens J (2013) A fuzzy set approach to assess the predictive accuracy of land use simulations, Ecological Modelling 261?262 pp. 32-42
Hagen-Zanker A (2008) Visualization and classification of urban change patterns on the basis of state-space transitions, pp. 1-3 Commission on GeoVisualization of the International Cartographic Association
Llano L, Chryssanthopoulos MK, Hagen-Zanker A, Rafiq MI (2013) Stochastic modeling of chloride-induced pitting corrosion of reinforcement bars in concrete, Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures - Proceedings of the 11th International Conference on Structural Safety and Reliability, ICOSSAR 2013 pp. 2659-2664
Chloride induced corrosion, caused primarily by salt spray in marine environments, airborne salts and de-icing salts, is one of the most common deterioration processes in reinforced concrete structures. At present, most of the models found in literature describe uniform corrosion and those that do address localized corrosion focus on a simplified definition of the reduced cross-sectional area of corroded rebars without due attention to physical characteristics and spatial variability. This may be attributed to the limitations of current manual methods used in evaluating the corrosion characteristics on the surface of reinforcement. In this paper, an automated procedure for the acquisition of corrosion depth data on rebars based on 3D laser scanning is investigated. Moreover, the first results of an analysis process based on image analysis using wavelet theory are presented. These results show a promising way of improving the classification of corrosion depths. This can be useful for the relation between spatial distribution of corrosion and mechanical properties of the corroded element. © 2013 Taylor & Francis Group, London.
Hagen-Zanker A (2012) A comparison of three urban models of land use, transport and activity: Are different modelling traditions really a world apart., pp. 337-338 Department of Civil Engineering of the University of Coimbra
Most metrics of urban spatial structure are snapshots, summarizing spatial structure at one particular moment in time. They are therefore not ideal for the analysis of urban change patterns. This paper presents a new spatio-temporal analytical method for raster maps that explicitly registers changesin patterns. The main contribution is a transition matrix which cross-tabulates the distance to the nearest urbanized location at the beginning and end of the analyzed period. The transition matrix by itself offers a powerful description of urban change patterns from which further metrics can be derived. In particular, a metric that is an indicator of the compactness of urban change is derived. The new metric is applied first to a synthetic dataset demonstrating consistency with existing classifications of urban change patterns. Next, the metric is applied country by country on the European CORINE land cover dataset. The results indicate a striking contrast in change patterns between Western and Eastern European counties. The method can be further elaborated in many different ways and can therefore be the first in a family of spatio-temporal descriptive statistics.
Hagen-Zanker A (2006) Map comparison methods that simultaneously address overlap and structure, Journal of Geographical Systems 8 pp. 165-185
Hagen A (2002) Multi-method assessment of map similarity, pp. 171-182 Universitat de les Illes Balears
After having set out the challenges connected with land ownership and real estate in the insular, micro context of Reunion Island, we plan to create a robot land-use model based on satellite images integrated with a cellular robot. Once the general framework of the modelling has been established, we will make the case for calibrating the cellular robot, and will discuss four scenarios in an approach to long-term territorial planning. La problématique de l'usage du sol à La Réunion.
Hagen-Zanker AH, guida (2014) A computational framework for scale-sensitive landscape pattern analysis,
Fuzzy set map comparison offers a novel approach to map comparison. The approach is specifically aimed at categorical raster maps and applies fuzzy set techniques, accounting for fuzziness of location and fuzziness of category, to create a similarity map as well as an overall similarity statistic: the Fuzzy Kappa. To date, the calculation of the Fuzzy Kappa (or K-fuzzy) has not been formally derived, and the documented procedure was only valid for cases without fuzziness of category. Furthermore, it required an infinitely large, edgeless map. This paper presents the full derivation of the Fuzzy Kappa; the method is now valid for comparisons considering fuzziness of both location and category and does not require further assumptions. This theoretical completion opens opportunities for use of the technique that surpass the original intentions. In particular, the categorical similarity matrix can be applied to highlight or disregard differences pertaining to selected categories or groups of categories and to distinguish between differences due to omission and commission.
We investigated the determinants of personal exposure concentrations black carbon (BC), ultrafine particle number concentrations (PNC), and particulate matter (PM1, PM2.5 and PM10) in different travel modes. We quantified the contribution of key factors that explain the variation of the previous pollutants in four commuting routes in London, each covered by four transport modes (car, bus, walk and underground). Models were performed for each pollutant, separately to assess the effect of meteorology (wind speed) or ambient concentrations (with either high spatial or temporal resolution). Concentration variations were mainly explained by wind speed or ambient concentrations and to a lesser extent by route and period of the day. In multivariate models with wind speed, the wind speed was the common significant predictor for all the pollutants in the above-ground modes (i.e., car, bus, walk); and the only predictor variable for the PM fractions. Wind speed had the strongest effect on PM during the bus trips, with an increase in 1 m s-1 leading to a decrease in 2.25, 2.90 and 4.98 ¼g m-3 of PM1, PM2.5 and PM10, respectively. PM2.5 and PM10 concentrations in car trips were better explained by ambient concentrations with high temporal resolution although from a single monitoring station. On the other hand, ambient 32 concentrations with high spatial coverage although lower temporal resolution predicted better the concentrations in bus trips, due to bus routes passing through streets with a high variability of traffic intensity. In the underground models, wind speed was not significant and line and type of windows on the train explained 42% of the variation of PNC and 90% of all PM fractions. Trains in the district line with openable windows had an increase in concentrations of 1684 cm-3 for PNC and 40.69 ¼g m-3 for PM2.5 compared with trains that has non-openable windows. The results from this work can be used to target efforts to reduce personal exposures of London commuters.
Weather-related disruption is a pressing issue for transport infrastructure in the UK, which is expected to aggravate due to climate change. Infrastructure managers, such as Network Rail, need to adapt to these changes, tackling the challenges brought about by wide-ranging uncertainties from various sources. This paper explores the relationship between climate change and bridge scour, identifying barriers to sustainable adaptation. Scour is the removal of riverbed material at bridge foundations due to hydraulic action and is the foremost cause of bridge failure in the UK and worldwide. A model is developed that simulates the causal chain from climate change to scour risk. This is applied to four case study bridges in Wales and the south-west of England, quantifying the effects of climate change and tracing key uncertainties in the process. Results show that the current scour risk models in Network Rail may be insensitive to increases in risk due to climate change. One way to tackle this may be to introduce models to assess absolute risk; current scour risk models are used only for the prioritisation of vulnerable sites.
People with low-income often experience higher exposures to air pollutants. We compared the exposure to particulate matter (PM1, PM2.5 and PM10), Black Carbon (BC) and ultrafine particles (PNC; 0.02-1 µm) for typical commutes by car, bus and underground from 4 London areas with different levels of income deprivation (G1 to G4, from most to least deprived). The highest BC and PM concentrations were found in G1 while the highest PNC in G3. Lowest concentrations for all pollutants were observed in G2. We found no systematic relationship between income deprivation and pollutant concentrations, suggesting that differences between transport modes are a stronger influence. The underground showed the highest PM concentrations, followed by buses and a much lower concentrations in cars. BC concentrations in the underground were overestimated due to Fe interference. BC concentrations were also higher in buses than cars because of a lower infiltration of outside pollutants into the car cabin. PNCs were highest in buses, closely followed by cars, but lowest in underground due to the absence of combustion sources. Concentration in the road modes (car and bus) were governed by the traffic conditions (such as traffic flow interruptions) at the specific road section. Exposures were reduced in trains with non-openable windows compared to those with openable windows. People from lower income deprivation areas have a predominant use of car, receiving the lowest doses (RDD
Bridge owners worldwide manage large numbers of assets with limited budgets through risk assessments, using asset-specific data. However, when managing a large stock of aging assets, maintaining robust and up-to-date data records can be challenging. This issue comes to the fore when trying to understand asset vulnerability to current and future weather events in the context of a changing climate. By using a sample of data on railway bridges in the UK, this paper explores uncertainty associated with raw data used in bridge scour risk assessments for bridge stocks and its interaction with climate change uncertainty. Results indicate that our ability to foresee climate change impacts is not only limited by the aleatory uncertainty of climate change projections; avoidable uncertainty in basic asset data can outweigh aleatory uncertainty by an order of magnitude. Some parameters, such as floodplain width and the width of abutments, were found to be both subject to high uncertainty and also very influential for the estimation of scour risk, leading to reduction in the confidence in scour risk assessments. This finding contrasts with the unchallenged assumption in the field that dimensions of bridge elements are not associated with uncertainty. The nature of scour implies that a potential increase in the frequency and severity of extreme weather events will increase scour risk. This paper shows that in order to be able to understand and account for this increase, scour management processes must effectively address data uncertainty. Active measures to control data quality would be an effective step towards understanding and managing bridge resilience in the context of current and future climatic conditions.
Increasingly, the application of models in urban hydrology has undergone a shift toward integrated structures that recognize the interconnected nature of the urban landscape and both the natural and engineered water cycles. Improvements in computational processing during the past few decades have enabled the application of multiple, connected model structures that link previously disparate systems together, incorporating feedbacks and connections. Many applications of integrated models look to assess the impacts of environmental change on physical dynamics and quality of landscapes. Whilst these integrated structures provide a more robust representation of natural dynamics, they often place considerable data requirements on the user, whereby data are required at contrasting spatial and temporal scales which can often transcend multiple disciplines. Concomitantly, our ability to observe complex, natural phenomena at contrasting scales has improved considerably with the advent of increasingly novel monitoring technologies. This has provided a pathway for reducing model uncertainty and improving our confidence in modeled outputs by implementing suitable monitoring regimes. This commentary assesses how component models of an exemplar integrated model have advanced over the past few decades, with a critical focus on the role of monitoring technologies that have enabled better identification of the key physical process. This reduces the uncertainty of processes at contrasting spatial and temporal scales, through a better characterization of feedbacks which then enhances the utility of integrated model applications.
Infrastructure operators are facing the challenges of managing assets under pressures from reduced budgets, aging infrastructure and increasing travel demand. This happens in the context uncertain climate change prompting the need for ever more robust and flexible decision support tools. One major risk to bridges in both current and future climate conditions is bridge scour- the removal of riverbed material at bridge foundations due to the flow of water. Scour is the foremost cause of bridge failure both in the UK and worldwide.
This thesis explores climate change impacts on the management of scour risk for national bridge stocks. To do this a selection of methods is compiled to model the chain of processes linking climate change to scour risk at a network level, exploring the role of key uncertainties.
One main research finding is that the current scour assessment techniques used in Network Rail may be insensitive to the effects of climate change. This is a result of a number of factors, including the use of over-conservative models, exceedance probabilities and safety factors. This conservatism is not well understood and leads to the reduced ability of Network Rail to objectively assess bridge scour risk at a network level, which has repercussions both in the context of current and future climate.
Another key finding is that climate change uncertainty, which is largely aleatory, may in some cases be overshadowed by asset uncertainties, which can be reduced. Some model inputs, such as floodplain width and abutment width, are found to be both subjected to high uncertainty and also influential for the estimation of scour risk, leading to reduction in the confidence in scour risk assessments. Understanding model sensitivities and the relevant uncertainties would enable bridge operators to improve the quality of scour risk assessments by improving the quality of relevant data.
This thesis makes a number of key recommendations that will enable Network Rail and other bridge stock managers to effectively adapt scour risk management practices for national bridge stocks to climate change.
Women are under-represented in commuter cycling in England and Wales. Consequently, women miss out on the health benefits of active commuting over distances where walking is less practical. Similarly, where cycling could replace motorised forms of transport, society is missing out on the wider health benefits associated with reductions in air pollution, road noise and social severance. This paper uses aggregate (ecological) models to investigate the reasons behind the gender gap in cycling. The relative attractiveness of cycling in different areas is described using a set of 17 determinants of commuter cycling mode share: distance, population density, cycle paths, cycle lanes, traffic density, hilliness, temperature, sun, rain, wind, wealth, lower social status, children, green votes, bicycle performance, traffic risk and parking costs. The correlation between these determinants and census-recorded cycling mode share is examined in logit models for commuters who work 2-5 km from home. The models explain a large share of the variation in cycling levels. There are small but significant differences in the importance of individual determinants between men and women. However, the gender gap is largely explained by a differentiated response to the relative attractiveness of an area for cycling, the sum effect of all determinants. The ratio of male to female cycling rates is greatest in areas that are less attractive for cycling, whereas in the most attractive areas the ratio approaches parity. On average, women require a more conducive environment for cycling than men. Since the typical environment in England and Wales is not conducive for cycling, women are under-represented in commuter cycling rates and miss out on the health dividend. The results suggest improvements to the cycling environment may be moderated by the existing attractiveness of the environment for cycling, with improvements in less attractive areas having a smaller absolute effect on cycling rates.
The bicycle is an efficient way to travel. There are individual and population-level health and wellbeing benefits that arise when more people cycle. However, cycling is rare in England and Wales and commuter cyclists are disproportionately likely to be male and middle aged (35 to 49). Society therefore misses out on the wider benefits of higher cycling levels, and women and certain age groups miss out on the individual level benefits.
This thesis uses geospatial analysis to examine cycling behaviours at multiple scales, seeking to understand the interactions between demographics and causal factors of commuter cycling mode share. It also examines the influence of vehicular traffic in detail and considers what actions local authorities might take to increase cycling levels.
Using both aggregate (area-based) and network (route based) modelling approaches, it identifies that the most important factors influencing cycling behaviours are hilliness, traffic, wealth, temperature and population density. Whilst these and other factors differ somewhat in their relative importance between demographic groups, differences in cycling rates are best explained by group-specific responses to the combined influence of all factors ? the relative utility of cycling. On average, women and older (>49) or younger (
Policy should work towards making urban areas compact, dense and traffic free, with vehicle speeds under 30kph and with suitable levels of cycling infrastructure along key corridors to work. Urban form should be designed primarily with female cyclists in mind and male cyclists will benefit accordingly.