Détail de l'auteur
Auteur Alex Hagen-Zanker |
Documents disponibles écrits par cet auteur (6)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externesA data-driven framework to manage uncertainty due to limited transferability in urban growth models / Jingyan Yu in Computers, Environment and Urban Systems, vol 98 (December 2022)
Titre : A data-driven framework to manage uncertainty due to limited transferability in urban growth models Type de document : Article/Communication Auteurs : Jingyan Yu, Auteur ; Alex Hagen-Zanker, Auteur ; Naratip Santitissadeekorn, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101892 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] automate cellulaire
[Termes IGN] changement d'utilisation du sol
[Termes IGN] croissance urbaine
[Termes IGN] estimation bayesienne
[Termes IGN] étalement urbain
[Termes IGN] Europe (géographie politique)
[Termes IGN] méthode de Monte-Carlo par chaînes de Markov
[Termes IGN] modèle stochastique
[Termes IGN] simulation dynamiqueRésumé : (auteur) The processes of urban growth vary in space and time. There is a lack of model transferability, which means that models estimated for a particular study area and period are not necessarily applicable for other periods and areas. This problem is often addressed through scenario analysis, where scenarios reflect different plausible model realisations based typically on expert consultation. This study proposes a novel framework for data-driven scenario development which, consists of three components - (i) multi-area, multi-period calibration, (ii) growth mode clustering, and (iii) cross-application. The framework finds clusters of parameters, referred to as growth modes: within the clusters, parameters represent similar spatial development trajectories; between the clusters, parameters represent substantially different spatial development trajectories. The framework is tested with a stochastic dynamic urban growth model across European functional urban areas over multiple time periods, estimated using a Bayesian method on an open global urban settlement dataset covering the period 1975–2014.
The results confirm a lack of transferability, with reduced confidence in the model over the validation period, compared to the calibration period. Over the calibration period the probability that parameters estimated specifically for an area outperforms those for other areas is 96%. However, over an independent validation period, this probability drops to 72%. Four growth modes are identified along a gradient from compact to dispersed spatial developments. For most training areas, spatial development in the later period is better characterized by one of the four modes than their own historical parameters. The results provide strong support for using identified parameter clusters as a tool for data-driven and quantitative scenario development, to reflect part of the uncertainty of future spatial development trajectories.Numéro de notice : A2022-799 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101892 Date de publication en ligne : 08/10/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101892 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101966
in Computers, Environment and Urban Systems > vol 98 (December 2022) . - n° 101892[article]
Titre : Calibration of cellular automata urban growth models from urban genesis onwards - a novel application of Markov chain Monte Carlo approximate Bayesian computation Type de document : Article/Communication Auteurs : Jingyan Yu, Auteur ; Alex Hagen-Zanker, Auteur ; Naratip Santitissadeekorn, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 101689 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse diachronique
[Termes IGN] automate cellulaire
[Termes IGN] changement d'utilisation du sol
[Termes IGN] Corine Land Cover
[Termes IGN] croissance urbaine
[Termes IGN] estimation bayesienne
[Termes IGN] Grande-Bretagne
[Termes IGN] méthode de Monte-Carlo par chaînes de Markov
[Termes IGN] modèle dynamiqueRésumé : (auteur) Cellular Automata (CA) models are widely used to study spatial dynamics of urban growth and evolving patterns of land use. One complication across CA approaches is the relatively short period of data available for calibration, providing sparse information on patterns of change and presenting problematic signal-to-noise ratios. To overcome the problem of short-term calibration, this study investigates a novel approach in which the model is calibrated based on the urban morphological patterns that emerge from a simulation starting from urban genesis, i.e., a land cover map completely void of urban land. The application of the model uses the calibrated parameters to simulate urban growth forward in time from a known urban configuration. This approach to calibration is embedded in a new framework for the calibration and validation of a Constrained Cellular Automata (CCA) model of urban growth. The investigated model uses just four parameters to reflect processes of spatial agglomeration and preservation of scarce non-urban land at multiple spatial scales and makes no use of ancillary layers such as zoning, accessibility, and physical suitability. As there are no anchor points that guide urban growth to specific locations, the parameter estimation uses a goodness-of-fit (GOF) measure that compares the built density distribution inspired by the literature on fractal urban form. The model calibration is a novel application of Markov Chain Monte Carlo Approximate Bayesian Computation (MCMC-ABC). This method provides an empirical distribution of parameter values that reflects model uncertainty. The validation uses multiple samples from the estimated parameters to quantify the propagation of model uncertainty to the validation measures. The framework is applied to two UK towns (Oxford and Swindon). The results, including cross-application of parameters, show that the models effectively capture the different urban growth patterns of both towns. For Oxford, the CCA correctly produces the pattern of scattered growth in the periphery, and for Swindon, the pattern of compact, concentric growth. The ability to identify different modes of growth has both a theoretical and practical significance. Existing land use patterns can be an important indicator of future trajectories. Planners can be provided with insight in alternative future trajectories, available decision space, and the cumulative effect of parcel-by-parcel planning decisions. Numéro de notice : A2021-616 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101689 Date de publication en ligne : 12/08/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101689 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98367
in Computers, Environment and Urban Systems > vol 90 (November 2021) . - n° 101689[article]
Titre : Adaptive zoning for transport mode choice modeling Type de document : Article/Communication Auteurs : Alex Hagen-Zanker, Auteur ; Ying Jin, Auteur Année de publication : 2013 Article en page(s) : pp 706 - 723 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] extensibilité
[Termes IGN] interaction spatiale
[Termes IGN] Londres
[Termes IGN] modélisation spatiale
[Termes IGN] outil d'aide à la décision
[Termes IGN] réseau de transport
[Termes IGN] zonage (urbanisme)Résumé : (Auteur) Adaptive zoning is a recently introduced method for improving computer modeling of spatial interactions and movements in the transport network. Unlike traditional zoning, where geographic locations are defined by one single universal plan of discrete land parcels or ‘zones’ for the study area, adaptive zoning establishes a compendium of different zone plans, each of which is applicable to one journey origin or destination only. These adaptive zone plans are structured to represent strong spatial interactions in proportionately more detail than weaker ones. In recent articles, it has been shown that adaptive zoning improves, by a large margin, the scalability of models of spatial interaction and road traffic assignment. This article confronts the method of adaptive zoning with an application of the scale and complexity for which it was intended, namely an application of mode choice modeling that at the same time requires a large study area and a fine-grained zone system. Our hypothesis is that adaptive zoning can significantly improve the accuracy of mode choice modeling because of its enhanced sensitivity to the geographic patterns and scales of spatial interaction. We test the hypothesis by investigating the performance of three alternative models: (1) a spatially highly detailed model that is permissible to the maximum extent by available data, but requires a high computational load that is generally out of reach for rapid turnaround of policy studies; (2) a mode choice model for the same area, but reducing the computational load by 90% by using a traditional zone system consisting of fewer zones; and (3) a mode choice model that also reduces the computational load by 90%, but based on adaptive zoning instead. The tests are carried out on the basis of a case study that uses the dataset from the London Area Transport Survey. Using the first model as a benchmark, it is found that for a given computational load, the model based on adaptive zoning contains about twice the amount of information of the traditional model, and model parameters on adaptive zoning principles are more accurate by a factor of six to eight. The findings suggest that adaptive zoning has a significant potential in enhancing the accuracy of mode choice modeling at the city or city-region scale. Numéro de notice : A2013-578 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2012.01372.x Date de publication en ligne : 14/01/2013 En ligne : https://doi.org/10.1111/j.1467-9671.2012.01372.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32714
in Transactions in GIS > vol 17 n° 5 (October 2013) . - pp 706 - 723[article]
Titre : An improved fuzzy Kappa statistic that accounts for spatial autocorrelation Type de document : Article/Communication Auteurs : Alex Hagen-Zanker, Auteur Année de publication : 2009 Article en page(s) : pp 61 - 73 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] autocorrélation spatiale
[Termes IGN] Kappa de Cohen
[Termes IGN] logique floue
[Termes IGN] voisinage (relation topologique)Résumé : (Auteur) 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. Copyright Taylor & Francis Numéro de notice : A2009-127 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810802570317 En ligne : https://doi.org/10.1080/13658810802570317 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29757
in International journal of geographical information science IJGIS > vol 23 n° 1-2 (january 2009) . - pp 61 - 73[article]Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 079-09011 RAB Revue Centre de documentation En réserve L003 Disponible 079-09012 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Further developments of a fuzzy set map comparison approach Type de document : Article/Communication Auteurs : Alex Hagen-Zanker, Auteur ; B. Straatman, Auteur ; I. Uljee, Auteur Année de publication : 2005 Article en page(s) : pp 769 - 785 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse comparative
[Termes IGN] carte numérique
[Termes IGN] classification dirigée
[Termes IGN] données maillées
[Termes IGN] estimation de précision
[Termes IGN] Kappa de Cohen
[Termes IGN] logique floue
[Termes IGN] matriceRésumé : (Auteur) 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. Numéro de notice : A2005-354 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810500072137 En ligne : https://doi.org/10.1080/13658810500072137 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27490
in International journal of geographical information science IJGIS > vol 19 n° 7 (august 2005) . - pp 769 - 785[article]Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 079-05071 RAB Revue Centre de documentation En réserve L003 Disponible 079-05072 RAB Revue Centre de documentation En réserve L003 Disponible Permalink
