Spatial Statistics: Emerging Patterns | Poster Programme

Poster Programme

Poster session 1 Wednesday, 10th June 2015 at 13:10-14:10

[P1.01] Spatial point pattern analysis for exploring the intraspecific interactions of eshnan (Seidlitzia rosmarinus) shrubs in Qehi protected area, central Iran Y. Erfanifard, E. Khosravi*, Shiraz University, Iran [P1.02] Mapping end-stage renal disease: Spatial variations on small area level and association with deprivation F. Occelli*1, M. Génin1, A. Deram1, C. Noël2, F. Glowacki2, D. Cuny1, 1Université Lille, France, 2CHRU de Lille, France [P1.03] Filtering Volunteered Geospatial information (VGI) using Spatial Point Pattern. Birds observer's credibility P. Aragó*1, P. Juan1, M. Saez2, D. Varga1, 1University Jaume I, Spain, 2University of Girona, Spain [P1.04] Spatial disaggregation of mortality data using penalized composite link mixed models D. Ayma Anza*1, M. Durbán Reguera1, D-J. Lee2, 1Universidad Carlos III de Madrid, Spain, 2Basque Center of Applied Mathematics, Spain [P1.05] Spatial modelling of extreme rainfall in northeast Thailand S. Yoon*1, B. Kumphon2, J-S. Park3, 1Weather Information Service Engine, Republic of Korea, 2Mahasarakham University, Thailand, 3Chonnam National University, Republic of Korea [P1.06] The effects of air pollution on mortality in South Korea J.O. Park1, S. Yoon*2, M.H. Na1, H-C. Song3, 1Chonnam National University, Republic of Korea, 2Weather Information Service Engine, Republic of Korea, 3Chonnam National University Hospital, Republic of Korea [P1.07] An author topic-based approach to cluster tweets and mine their location M. Morchid1, Y. Portilla*1, D. Josselin1 ,2, R. Dufour1, E. Altman3, M. El-Beze1, J-V. Cossu1, G. Linares1, A. Reiffers- Masson1, 1University of Avignon, France, 2UMR ESPACE 7300, France, 3INRIA, France [P1.08] Predictive modelling of seismic hazard applying naïve Bayes and granular computing classifiers H. Sheikhian1, M.R. Delavar1, A. Stein*2, 1University of Tehran, Iran, 2University of Twente, The Netherlands [P1.09] Spatially Balanced Sampling: Application to environmental surveys J.A. Brown*1, B.L. Robertson1, T. McDonald2, 1University of Canterbury, New Zealand, 2Western Ecosystems Technology Inc., USA [P1.10] spatio-temporal analysis for bird migration phenology using citizen science data A. Arab*1, J.R. Courter2, J. Zelt3, 1Georgetown University, USA, 2Malone University, USA, 3North American Bird Phenology Program, USA [P1.11] Density-based human mobility clusters and 2014 Ebola epidemic spread in West Africa K. Sallah*, R. Giorgi, J. Gaudart, Aix-Marseille Université, France [P1.12] Analysis and modeling spatial and spatial-ontogenetic structure of old-growth boreal forests by random point process models with hierarchical interactions P. Grabarnik*1, J. Heikkinen2, A. Aleinikov3, 1Russian Academy of Sciences, Russia, 2Natural Resources Institute Finland (Luke), Finland, 3Centre for problems of ecology and productivity of forests (RAS), Russia [P1.13] Predicting the potential distribution and ecological effects of the invasion of Lupinus polyphyllus (Lindl.) in Germany and beyond V.M.S. Vetter*1, A. Jentsch2, C. Buhk1, 1University Koblenz-Landau, Germany, 2University Bayreuth, Germany [P1.14] Filtering and mapping public health data with an innovative kriging approach, accounting for single observation variance V. Casella*1, A. Manzino2, R. Bellazzi1, M. Franzini1, 1University of Pavia, Italy, 2Polytechnic of Torino, Italy [P1.15] Small area estimation of diagnosed and undiagnosed diabetes prevalence in the US using BRFSS and NHANES data L. Dwyer-Lindgren*, M. Ng, A.D. Flaxman, A.H. Mokdad, Institute for Health Metrics and Evaluation, University of Washington, USA [P1.16] Windowed FLP-ETAS model with application to the Chilean seismic catalogs O. Nicolis*1, M. Chiodi2, G. Adelfio2, 1University of Valparaiso, Chile, 2University of Palermo, Italy [P1.17] Spatial-temporal modelling of under-5 mortality using survey data with different levels of spatial aggregation L. Dwyer-Lindgren*, D.A. Roberts, A.D. Flaxman, S.S. Lim, University of Washington, USA Spatial Statistics: Emerging Patterns | Poster Programme

[P1.18] Mapping the distribution of marine birds in the Northeast and Mid-Atlantic using a space-time double- hurdle model E. Balderama*1, B. Gardner2, B. Reich2, 1Loyola University Chicago, USA, 2North Carolina State University, USA [P1.19] Spatial distribution estimation of malaria in Northern China with genetic programming under climate change scenarios Y.Z. Song1 ,2, Y. Ge*2 ,3, J.F. Wang2, J.H. Peng1, Z.P. Ren2, Y.L. Liao2, 1China University of Geosciences (Beijing), China, 2Chinese Academy of Sciences, China, 3Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, China [P1.20] An adaptation of profile regression to spatial data to assess long term effects of metals from particulate matter on health A. Lavigne*2 ,1, M. Blangiardo1, K. de Hoogh1, N. Best1, A. Hansell1, 1Imperial College, UK, 2Université de Lille, France [P1.21] Flood risk vulnerability assessment: what are the main factors? Classification and relative contribution of the main factors of flood risk vulnerability at a regional level. G. Jouannic*, T. Legendre, P. Gastaud, Z. Kolli, M. Marchetti, D. Felts, Cerema, France [P1.22] Spatial distribution of the dengue vector aedes aegypti in rural areas of anapoima and la mesa municipalities, central colombia L. Cabezas*1, W. Cabanzo2, F. Santa2, V.A. Olano1, D. Sarmiento1, S. Vargas1, J.F. Jaramillo1, T.A. Stenstrom3, H. Overgaard4 ,5, M.I. Matiz1, 1Universidad El Bosque, Colombia, 2Universidad Distrital Francisco José de Caldas, Colombia, 3Durban University of Technology, South Africa, 4Norwegian University of Life Sciences, Norway, 5Montpellier Cedex 5, France [P1.23] Substitute CT generation using Markov random field mixture models A.G.F. Hildeman*1, D. Bolin1, J. Wallin1, A. Johansson2, T. Nyholm2, T. Asklund2, J. Yu2, 1Chalmers University of Technology, Sweden, 2Umeå University, Sweden [P1.24] A coregionalization model to assist the selection process of local and global variables in semiparametric geographically weighted poisson regression M.C. Ribeiro*, A.J. Sousa, M.J. Pereira, Universidade de Lisboa, Portugal [P1.25] “Eurovisioness” as a measure of spatial dependence: revision of economic growth L. Sattarova, Goethe University of Frankfurt, Germany [P1.26] Increasing the depth of current understanding: sensitivity tests of larval dispersal models for ecologists R.E. Ross*1, W.A.M. Nimmo-Smith1, K.L. Howell1, 1Plymouth University, UK, 2Plymouth University, UK, 3Plymouth University, UK [P1.27] Spatio-temporal analysis of remote sensing and field measurements for smart farming M. van Persie1, H.H.N. Noorbergen1, B. van de Kerkhof*1, L. Schouten2, R. Ghauharali3, 1National Aerospace Laboratory, The Netherlands, 2Infram BV, The Netherlands, 3VB Ecoflight BV, The Netherlands [P1.28] Where did all the points go? C.M. Jones-Todd*, J.B. Illian, St Andrews University, UK [P1.29] A copula-based habit environment index for fish spatial population models C. Marsh1, N. Sibanda*1, M. Dunn1, A. Dunn2, 1Victoria University of Wellington, New Zealand, 2National Institute of Water and Atmospheric Research, New Zealand [P1.30] Tessellation-based segmentation for isolating mesoscale oceanic eddies from satellite observation Q. Wu, University College London, UK [P1.31] Spatial species interactions in cloud forests C. Díaz-Ávalos*, N.R. Mejía-Domínguez, Universidad Nacional Autonoma de Mexico, Mexico [P1.32] Prediction model of traffic accident points in consideration of probe-car data S. Tatsuki*, F. Tomoyuki, Keio University, Japan [P1.33] Spatial distribution of Cervical Cancer Incidence and socio-economic conditions in San Luis Potosí State, Mexico. M. Terán-Hernández*1, R. Ramis-Prieto2, J. Calderón-Hernández1, M. Aguilar-Robledo1, 1Universidad Autónoma dev San Luis Potosí, Mexico, 2National Centre for Epidemiology, Carlos III Institute of Health, Spain [P1.34] Poisson spatial regression model to study gastric cancer in Boyaca department, Colombia in 2005 F. Sarmiento, F. Santa*, Universidad Distrital Francisco Jose De Caldas, Colombia [P1.35] Estimation of multivariable and multivariate spatial variability for child adiposity measures in rural South African households E. Musenge*1, L. Kimani-Murage2, S.A. Norris1, K. Kahn1 ,2, 1University of the Witwatersrand, South Africa, Spatial Statistics: Emerging Patterns | Poster Programme

2African Population and Health Research Centre, Kenya, 3Centre for Global Health Research, Sweden, 4INDEPTH Network, Ghana [P1.36] Association between visceral leishmaniasis social indicators in the city of Campo Grande, Brazil E.F. Oliveira1, A.G. Oliveira2, P.M. Batista2, M.J. Medeiros*1 ,3, 1Universidade de São Paulo, Brazil, 2Universidade Federal de Mato Grosso do Sul, Brazil, 3Universidade Federal do Rio de Janeiro, Brazil [P1.37] Modelling spatial relationship between climatic conditions and annual parasite incidence of malaria S. Elmogy*, N. Zeft, Cairo University, Egypt [P1.38] A Bayesian modelling proposal for highly multivariate disease mapping M.A. Martinez-Beneito*1, P. Botella Rocamora1, S. Banerjee1, 1FISABIO-Public Health, Spain, 2University CEU- Cardenal Herrera, Spain, 3University of California, Los Angeles, USA [O2.25] Spatial patterns of links between temperature extremes and cardiovascular health in the Czech Republic A. Urban1,2, J. Kysely*1 1Institute of Atmospheric Physics AS CR, Prague, Czech Republic, 2Charles University, Czech Republic

Poster session 2 Thursday, 11th June 2015 at 13:30-14:30

[P2.01] Error rates in multi-category classification of the spatial multivariate Gaussian data L. Dreiziene*1 ,2, K. Ducinskas2, 1Vilnius University, Lithuania, 2Klaipeda University, Lithuania [P2.02] Using bootstrap methods to investigate coefficient non-stationarity in regression models P. Harris*1, C. Brunsdon2, I. Gollini3, T. Nakaya4, M. Charlton2, 1Rothamsted Research, UK, 2Maynooth University, Ireland, 3University of Bristol, UK, 4Ritsumeikan University, Japan [P2.03] A novel approach to map soil organic carbon content using spectroscopic and environmental data M. Rial-Tubío*, A. Martínez-Cortizas, L. Rodríguez-Lado, Universidade de Santiago de Compostela, Spain [P2.04] A random forest model to map soil bulk density from limited data L. Rodríguez-Lado*, M. Rial-Tubío, T. Taboada-Rodríguez, A. Martínez-Cortizas, Universidade de Santiago de Compostela, Spain [P2.05] Euclidean distance versus travel time in business location: A probabilistic mixture of hurdle-Poisson models S. Buczkowska*1, N. Coulombel1, M. Lapparent (de)1, 1French Institute of Science and Technology for Transport, Development and Networks, France, 2Ecole des Ponts ParisTech, France, 3Université Paris-Est, France, 4Ecole Polytechnique Fédérale de Lausanne, Switzerland [P2.06] Global mean estimation using a self-organizing dual-zoning method for preferential sampling Y.C. Pan*1 ,2, B.B. Gao1 ,2, X.H. Ren1 ,2, Y. Liu1 ,2, Y.B. Gao1 ,2, 1National Engineering Research Center for Information Technology in Agriculture, China, 2Key Laboratory for Information Technologies in Agriculture, the Ministry of Agriculture, China [P2.07] Gridding and calibrating ensemble wind forecasts in the boundary layer M. Zamo*1, M. Taillardat1, O. Mestre1, L. Bel2, P. Naveau3, 1Météo-France, France, 2AgroParisTech, France, 3LSCE, France [P2.08] Geographically weighted regression for spatial patterns of CO2 emission in Seoul metropolitan city D.H. Kim, K.Y. Kang, S.Y. Sohn*, Yonsei university, Republic of Korea [P2.09] Cross-validation estimations of hyper-parameters of gaussian processes with inequality constraints H. Maatouk*1, O. Roustant1, Y. Richet2, 1Mines Saint-Étienne, France, 2Institut de Radioprotection et de Sûreté Nucléaire, France [P2.10] Global influence diagnostics in gaussian spatial linear model with multiple repetitions F. De Bastiani*1, M.A. Uribe Opazo1 ,2, A.H.M.A. Cysneiros1, M. Galea1 ,3, 1Universidade Federal de Pernambuco, Brazil, 2Universidade Estadual do Oeste do Paraná, Brazil, 3Pontificia Universidad Catolica de Chile, Chile [P2.11] A New Latent Class to Fit Spatial Econometrics Models with Integrated Nested Laplace Approximations V. Gómez-Rubio1, R.S. Bivand*2 ,4, H. Rue3, 1Universidad de Castilla-La Mancha, Spain, 2Norwegian School of Economics, Norway, 3Norwegian University for Science and Technology, Norway, 4Adam Mickiewicz University, Poland [P2.12] Continuous Bayesian networks vs. other methods for regression in environmental modelling A.D. Maldonado*, R.F. Ropero, P.A. Aguilera, A. Fernández, R. Rumí, A. Salmerón, University of Almería, Spain [P2.13] Modelling spatial structure of apartment prices: an empirical study in six French cities Spatial Statistics: Emerging Patterns | Poster Programme

D. Otroshchenko*, A. Simon, Université Paris Dauphine, France [P2.14] Linear spatial modelling and co-kriging of collocated data: An application to precipitation and temperature data E. Asa*1 ,2, J. Memba2, G. Padmanabhan2, 1Minnesota State University, USA, 2North Dakota State University, USA [P2.15] Spatial stochastic model for predicting topsoil organic carbon content over a cultivated periurban region, using soil properties, a digital elevation model and remote sensing M. Zaouche*1 ,2, E. Vaudour1 ,2, L. Bel1 ,2, J. Tressou2, 1AgroParisTech, France, 2INRA, France [P2.16] An adaptation of the covariance modeling for large scale geostatistics estimation in Air Quality M. Beauchamp*1, L. Malherbe1, C. de Fouquet2, 1INERIS, France, 2Mines ParisTech, Geosciences, France [P2.17] Ordinary least squares regression method approach for site selection of automated teller machines (ATMs) K. Bilginol*, H.H. Denli, D.Z. Seker, Istanbul Technical University, Turkey [P2.18] Spatial distribution patterns and influencing factors of poverty - a case study on key country from national contiguous special poverty-stricken areas in China L. Sun, Chinese Academy of Agricultural Engineering, China [P2.19] Pollutant monitoring network changes R.I. Smith*, L. Banin, C. Brabin, D. Fowler, Centre for Ecology and Hydrology, UK [P2.20] Compositional data model considering spatial dependency T. Yoshida*, M. Tsutsumi, University of Tsukuba, Japan [P2.21] Implementation of fast and accurate algorithms for the approximation of MVN probabilities for big sample data D. Martinetti*, G. Geniaux, INRA Ecodeveloppement UR 767, France [P2.22] An adaptive spatial model for satellite-based precipitation data over large region A. Chakraborty*1, S. De4, K.P. Bowman2, H. Sang2, M.G. Genton3, B.K. Mallick2, 1University of Arkansas, USA, 2Texas A&M University, USA, 3King Abdullah Institute of Science and Technology, Saudi Arabia, 4SAS Research and Development India, India [P2.23] MLE for panel count data models with spatio-temporal dynamics: An application to urban crime R.L. Liesenfeld1, J.F.R. Richard2, J.V. Vogler*1, 1University of Cologne, Germany, 2University of Pittsburgh, USA [P2.24] Spatial variation of drivers of agricultural abandonment with spatially boosted models M. Schneider*1 ,2, G. Blanchard1, C. Levers2, T. Kuemmerle2, 1Insitute of Mathematics, University of Potsdam, Germany, 2Institute of Geography, Humboldt University of Berlin, Germany [P2.25] R as a GIS: illustrating scale and aggregation problems with forest fires data R. Louvet*1, J. Aryal2, D. Josselin1 ,3, C. Genre-Grandpierre1, 11. UMR ESPACE 7300 CNRS, Université de Nice Sophia-Antipolis, France, 22. UTAS, University of Tasmania, Australia, 33. Laboratoire d’Informatique d’Avignon, Université d’Avignon et des Pays de Vaucluse, France [P2.26] Mapping and modelling soil carbon in the grasslands of British Columbia, Canada H.J. Richardson*, L. Fraser, D. Hill, Thompson Rivers University, Canada [P2.27] An evaluation of spatially-constrained regionalization routines M.V. Janikas*1, J.C. Duque2, L.H. Chin1, 1ESRI, USA, 2Universidad EAFIT, Colombia [P2.28] Time series analysis of geodetic observations to study GPS stations’ displacement trends in Colombia S. Lizarazo1, F. Santa*2, H. Mora1, 1Servicio Geologico Colombiano, Colombia, 2Universidad Distrital Francisco Jose De Caldas, Colombia [P2.29] WITHDRAWN [P2.30] WITHDRAWN [P2.31] New technique in spatial analysis of basin morphometric parameters A.A. Beg, University of Mustansiriyah, College of Education, Iraq [P2.32] Adaptation of a hidden markov model by explain the spatial dependence of the criminals dynamics in post- conflict stage A. Mendoza*, D. Suarez, UNODC, Colombia [P2.33] Bootstrap test for anisotropic detection D.F. Rossoni*1, R.R. Lima2, M.S. Oliveira2, 1State University of Maringa (UEM), Brazil, 2Federal University of Lavras (UFLA), Brazil [P2.34] Spatial autocorrelation and the solution to the p-median problem Spatial Statistics: Emerging Patterns | Poster Programme

P. Sinha*, D.A. Griffith, University of Texas at Dallas, USA [P2.35] A methodological framework to decipher the morphogenesis mechanisms in Arabodopsis thaliana leaves J. Burguet*, E. Biot, IJPB UMR1318 INRA-AgroParisTech, France [P2.36] Spatial patterns in the rate of alcohol withdrawal syndrome in Galicia (Spain) J. Espasandín-Domínguez*, I. Guler, M.P Pata, F. Gude, A. González-Quintela, C. Cadarso-Suárez, University of Santiago de Compostela, Spain [P2.37] Bayesian additive regression models for modeling spatial patterns of distribution of mussel seed, in presence of different sources of overdispersion M.P. Pata*, C. Cadarso-Suárez, V. Lustres-Pérez, University of Santiago de Compostela, Spain [P2.38] Applying Binary Structured Additive Regression (STAR) for predicting wildfire in Galicia, Spain L. Ríos-Pena*1, C. Cadarso-Suárez2, T. Kneib3, M. Marey-Pérez1, 1Estación Biológica de Doñana (EBD-CSIC), Spain, 2University of Santiago de Compostela, Spain, 3Georg-August-Universität Göttingen, Germany [P2.39] Predictive performance of geoadditive survival models tostudy geographical patterns in coronary heart disease I. Guler*1, M. Rodríguez-Girondo2, J. Espasandín-Domínguez1, F. Gude1, C. Cadarso-Suárez1, 1University of Santiago de Compostela, Spain, 2Leiden University Medical Center, The Netherlands

Poster session 3 Friday, 12th June 2015 at 13:30-14:30

[P3.01] Modelling the depdence of spatio-temporal clustering on scale Q.L. Liu*1, J.B. Tang1, M. Deng1, K. Tao2, 1Central South University, China, 2Geomatics Center of Hunan Province, China [P3.02] Covariance tapering for multivariate Gaussian random fields estimation M. Bevilacqua1, A. Fasso3, C. Gaetan4, E. Porcu2, D. Velandia*1, 1University of Valparaíso, Chile, 2University Técnica Federico Santa Maria, Chile, 3University Degli Studi Bergamo, Italy, 4University Ca'Foscari, Italy [P3.03] Estimating pooled within-time series variograms with spatially shifted temporal points A.K. Bhowmik*1, P. Cabral1, 1University of Koblenz-Landau, Germany, 2Universidade Nova de Lisboa, Portugal [P3.04] Visualization and analysis on the spatial-temporal patterns of flow direction of interprovincial migration in China based on origin-destination matrix J.H. Qi*1 ,2, Z. Wang1 ,2, Y.J. Wang1, D.C. Li1, 1Chinese Academy of Sciences, China, 2University of Chinese Academy of Sciences, China [P3.05] Techniques for analyzing the relationship between population density and geographical features of Interest A. Johnson*1 ,2, C. Arrowsmith1, 1RMIT, Australia, 2MCRI, Australia [P3.06] Spatial patterning of urban wetland dynamics: An indicator of human and climate impacts W. Ji, University of Missouri - Kansas City, USA [P3.07] Spatio-temporal modelling of a forest spanning 50 years - the effects of different thinning strategies S. O'Rourke*, G.E. Kelly, University College Dublin, Ireland [P3.08] Calibrating a geographically weighted regression model with parameter-specific distance metrics B. Lu*1, P. Harris2, M. Charlton3, C. Brunsdon3, 1Wuhan University, China, 2Rothamsted Research, UK, 3Maynooth University, Ireland [P3.09] Robust estimation of spatio-temporal distribution of slow slip event by switching model T. Araki*, T. Ochi, N. Matsumoto, S. Akaho, National Institute of Advanced Industrial Science and Technology, Japan [P3.10] Impact of statistical mean methods on the trend of Antarctic sea ice Z.Y. Shi1, X. Zhao*1, X.P. Pang1, A. Stein1 ,2, 1Wuhan University, China, 2Twente University, The Netherlands [P3.11] A spatio-temporal parameter-driven model for Poisson counts C.E. Utazi, University of Southampton, UK [P3.12] Temporal statistical analysis of urban heat islands at the microclimate level P. Wong*1, P.C. Lai1, M. Hart2, 1The University of Hong Kong, Hong Kong, 2The University of New South Wales, Australia [P3.13] Vertical variation in the microclimates of a narrow street canyon and an open street P. Wong*1, W. Cheng1, B. Barratt2, P.C. Lai1, 1The University of Hong Kong, Hong Kong, 2King’s College London, Spatial Statistics: Emerging Patterns | Poster Programme

UK [P3.14] Crop area estimation from UAV transects and moderate spatial resolution image using spatial sampling method K.J. Shen*, Z.Y. Pei, F. Wang, X-Q. Zhang, G-N. Sun, X.W. Chen, S.J. Ma, Chinese Academy of Agricultural Engineering, China [P3.15] Choice between autocorrelation and stratification based estimators of spatial mea J.F. Wang*1 ,2, B.B. Gao1, 1Chinese Academy of Sciences, China, 2Chinese Center for Disease Control and Prevention, China [P3.16] Bayesian spatio-temporal kriging with misspecified black-box P.A. Faye*, P. Druilhet, N. Azzaoui, A.F. Yao, Blaise Pascal university - Laboratory of mathematics UMR 6620- CNRS, France [P3.17] Discovery of spatial patterns using dimension-induced clustering algorithm M. Kanevski, IDYST, University of Lausanne, Switzerland [P3.18] A coherence measure of association between LISA functions in spatial point patterns F.J. Rodríguez-Cortés*1, A.K. Mishra2, J. Mateu1, J.A. González1, 1Jaume I University, Spain, 2University of Connecticut, USA [P3.19] SCAT-SAR soil water index: How data matching impacts the fusion of scale-spanning remotely sensed soil moisture datasets B. Bauer-Marschallinger*, C. Paulik, W. Wagner, A. Gruber, M. Vreugdenhil, W. Dorigo, Vienna University of Technology, Austria [P3.20] Functional PCA for remotely sensed lake surface water temperature data M. Gong*, C. Miller, M. Scott, University of Glasgow, UK [P3.21] Modelling varicella incidence in Valencia, Spain A. Iftimi*1, J. Mateu2, F. Montes1, 1University of Valencia, Spain, 2University Jaime I, Castellon, Spain [P3.22] Spatial functional classification in a SARH(1) context J. Álvarez-Liébana*, M.D. Ruiz-Medina, University of Granada, Spain [P3.23] Prototypes of replicated spatio-temporal point patterns J.A. González*, J. Mateu, F.J. Rodriguez-Cortés, Uneversity Jaume I, Spain [P3.24] Sparse approximate inference for spatio-temporal point process models B. Cseke1, A. Zammit-Mangion*2, G. Sanguinetti1, T. Heskes3, 1University of Edinburgh, UK, 2University of Wollongong, Australia, 3Radboud University, The Netherlands [P3.25] k- co- occurrences density map estimation D.G. Leibovici*1, D. Brosset2, C. Claramunt2, M. Jackson1, 1University of Nottingham, UK, 2Naval Academy Research Institute, France

[P3.26] Data fusion of remote-sensing and in-lake chlorophylla data using statistical downscaling C.J. Wilkie*, E.M. Scott, C. Miller, University of Glasgow, UK [P3.27] WITHDRAWN [P3.28] Analysing fires and their socio economic factors in Sardinia L. Serra*1 ,2, C. Detotto1 ,3, M. Vannini1 ,3, 1Sassari University, Italy, 2CIBER of Epidemiology and Public Health, Spain, 3CRENoS, Italy [P3.29] Defining the spatio-temporal variability of public transport connectivity by integrating Google Transit data in GIS K. Fransen*, T. Neutens, P. De Maeyer, G. Deruyter, Ghent University, Belgium [P3.30] Multidimensional land cover change analysis using vector change and land cover taxonomies H. Arenas*, B. Harbelot, C. Cruz, University of Burgundy, France [P3.31] Statistical modelling of spatio-temporal data based on spatial interpolation of time series parameters L. Paulioniene, Klaipeda University, Lithuania [P3.32] Implementing approximations to extreme eigenvalues and eigenvalues of irregular surface partitionings for use in SAR and CAR models D.A. Griffith1, R.S. Bivand*2 ,3, Y. Chun1, 1University of Texas at Dallas, USA, 2Norwegian School of Economics, Norway, 3Adam Mickiewicz University, Poland [P3.33] Developments of rtop - interpolation of time series and simulation of data with a variable spatial support J.O. Skøien*1, G. Blösch2, G. Laaha3, J. Parajka2, E. Pebesma4, A. Viglione2, 1European Commission - Joint Research Centre, Italy, 2Vienna University of Technology, Austria, 3University of Natural Resources and Life Spatial Statistics: Emerging Patterns | Poster Programme

Sciences, BOKU Vienna, Austria, 4Westfälische Wilhelms-Universität Münster, Germany [P3.34] Epidemic spread and network structure estimations: The Case of the ISA virus episode in the Chilean salmon industry F. Pinochet, J. Quiroz*, Jorge Quiroz C. & Associated Consultants, Chile [P3.35] Representation of stochastic populations J. Houssineau*, D.E. Clark, Heriot-Watt University, UK [P3.36] Gridded station temperature data for validation of the climate models present climate M. Perčec Tadić*1, M. Kilibarda1, 1Meteorological and Hydrological Service, Croatia, 2Faculty of Civil Engineering, University of Belgrade, Serbia [P3.37] Developing a spatial analytical framework based on network k-functions – a case study in crash data analysis G. Khan*1, M. Chitturi2, A.R. Bill2, D.A. Noyce2, 1California State University Sacramento, USA, 2University of Wisconsin-Madison, USA [P3.38] Modelling resource selection across multiple spatial scales using varying coefficient regression T. Cornulier*1, A. Villers2, 1University of Aberdeen, UK, 2CEBC-CNRS, France [P3.39] Spatio-Temporal analysis of locations affected by floods in Bogota for the period 2001 - 2011 A. Sanchez, F. Santa*, L. Castillo, Universidad Distrital Francisco Jose De Caldas, Colombia [P3.40] On the similarity of spatial point sets: ordered and unordered cases X. Zhang, Wuhan University, China [P3.41] Advanced spatio-temporal wind power forecasting with distributed wind farms as sensors R. Girard*, G. Agoua, G. Kariniotakis, MINES ParisTech, France [P3.42] Some relevant spatial modelling and forecasting problems for wind power generation A. Lenzi*, G. Guillot, P. Pinson, Technical University of Denmark, Denmark [P3.43] Establishment of detection and correction parameters for a geostatistical homogenisation approach S. Ribeiro*1, J. Caineta1, A.C. Costa1, A. Soares2, 1Universidade Nova de Lisboa, Portugal, 2Universidade de Lisboa, Portugal [P3.44] Uncertainty assessment of a climate data homogenisation process based on geostatistical simulation J. Caineta1, S. Ribeiro1, A.C. Costa*1, A. Soares2, 1Universidade Nova de Lisboa, Portugal, 2Universidade de Lisboa, Portugal [P3.45] Statistical comparison of 3D point pattern distributions J. Burguet*1, P. Andrey1, 1IJPB UMR1318 INRA-AgroParisTech, France, 2UPMC Univ Paris 06, France