Relevant bibliographies by topics / Spatial point patterns

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Spatial point patterns'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Spatial point patterns"

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Ayala, G., I. Epifanio, A. Simó, and V. Zapater. "Clustering of spatial point patterns." Computational Statistics & Data Analysis 50, no. 4 (February 2006): 1016–32. http://dx.doi.org/10.1016/j.csda.2004.10.013.

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Symanzik, Jürgen. "Statistical Analysis of Spatial Point Patterns." Technometrics 47, no. 4 (November 2005): 516–17. http://dx.doi.org/10.1198/tech.2005.s318.

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Solow, Andrew R. "Bootstrapping Sparsely Sampled Spatial Point Patterns." Ecology 70, no. 2 (April 1989): 379–82. http://dx.doi.org/10.2307/1937542.

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Katti, S. K., Peter J. Diggle, and Brian D. Ripley. "Statistical Analysis of Spatial Point Patterns." Journal of the American Statistical Association 81, no. 393 (March 1986): 263. http://dx.doi.org/10.2307/2288020.

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Pellegrini, Pasquale A., and Steven Reader. "Duration Modeling of Spatial Point Patterns." Geographical Analysis 28, no. 3 (September 3, 2010): 219–43. http://dx.doi.org/10.1111/j.1538-4632.1996.tb00932.x.

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Schilcher, Udo, Günther Brandner, and Christian Bettstetter. "Quantifying inhomogeneity of spatial point patterns." Computer Networks 115 (March 2017): 65–81. http://dx.doi.org/10.1016/j.comnet.2016.12.018.

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ARAÚJO, Edmary Silveira Barreto, João Domingos SCALON, and Lurimar Smera BATISTA. "EXPLORATORY SPECTRAL ANALYSIS IN THREE-DIMENSIONAL SPATIAL POINT PATTERNS." REVISTA BRASILEIRA DE BIOMETRIA 39, no. 1 (March 31, 2021): 177–93. http://dx.doi.org/10.28951/rbb.v39i1.524.

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A spatial point pattern is a collection of points irregularly located within a bounded area (2D) or space (3D) that have been generated by some form of stochastic mechanism. Examples of point patterns include locations of trees in a forest, of cases of a disease in a region, or of particles in a microscopic section of a composite material. Spatial Point pattern analysis is used mostly to determine the absence (completely spatial randomness) or presence (regularity and clustering) of spatial dependence structure of the locations. Methods based on the space domain are widely used for this purpose, while methods conducted in the frequency domain (spectral analysis) are still unknown to most researchers. Spectral analysis is a powerful tool to investigate spatial point patterns, since it does not assume any structural characteristics of the data (ex. isotropy), and uses only the autocovariance function, and its Fourier transform. There are some methods based on the spectral frameworks for analyzing 2D spatial point patterns. There is no such methods available for the 3D situation and, therefore, the aim of this work is to develop new methods based on spectral framework for the analysis of three-dimensional point patterns. The emphasis is on relating periodogram structure to the type of stochastic process which could have generated a 3D observed pattern. The results show that the methods based on spectral analysis developed in this work are able to identify patterns of three typical three-dimensional point processes, and can be used, concurrently, with analyzes in the space domain for a better characterization of spatial point patterns.
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OGATA, Yosihiko, and Masaharu TANEMURA. "THE LIKELIHOOD ANALYSIS FOR SPATIAL POINT PATTERNS." Japanese Journal of Biometrics 8, no. 1 (1987): 1_27–38. http://dx.doi.org/10.5691/jjb.8.1_27.

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HöUgmander, Harri, and Aila SäUrkkä. "Multitype Spatial Point Patterns with Hierarchical Interactions." Biometrics 55, no. 4 (December 1999): 1051–58. http://dx.doi.org/10.1111/j.0006-341x.1999.01051.x.

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Baddeley, Adrian, and Rolf Turner. "Practical maximum pseudolikelihood for spatial point patterns." Advances in Applied Probability 30, no. 2 (June 1998): 273. http://dx.doi.org/10.1017/s000186780004698x.

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Dissertations / Theses on the topic "Spatial point patterns"

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Moradi, Mohammad Mehdi. "Spatial and spatio-temporal point patterns on linear networks." Doctoral thesis, Universitat Jaume I, 2018. http://hdl.handle.net/10803/664140.

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A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information Systems
The last decade witnessed an extraordinary increase in interest in the analysis of network related data and trajectories. This pervasive interest is partly caused by a strongly expanded availability of such datasets. In the spatial statistics field, there are numerous real examples such as the locations of traffic accidents and geo-coded locations of crimes in the streets of cities that need to restrict the support of the underlying process over such linear networks to set and define a more realistic scenario. Examples of trajectories are the path taken by moving objects such as taxis, human beings, animals, etc. Intensity estimation on a network of lines, such as a road network, seems to be a surprisingly complicated task. Several techniques published in the literature, in geography and computer science, have turned out to be erroneous. We propose several adaptive and non-adaptive intensity estimators, based on kernel smoothing and Voronoi tessellation. Theoretical properties such as bias, variance, asymptotics, bandwidth selection, variance estimation, relative risk estimation, and adaptive smoothing are discussed. Moreover, their statistical performance is studied through simulation studies and is compared with existing methods. Adding the temporal component, we also consider spatio-temporal point patterns with spatial locations restricted to a linear network. We present a nonparametric kernel-based intensity estimator and develop second-order characteristics of spatio-temporal point processes on linear networks such as K-function and pair correlation function to analyse the type of interaction between points. In terms of trajectories, we introduce the R package trajectories that contains different classes and methods to handle, summarise and analyse trajectory data. Simulation and model fitting, intensity estimation, distance analysis, movement smoothing, Chi maps and second-order summary statistics are discussed. Moreover, we analyse different real datasets such as a crime data from Chicago (US), anti-social behaviour in Castell´on (Spain), traffic accidents in Medell´ın (Colombia), traffic accidents in Western Australia, motor vehicle traffic accidents in an area of Houston (US), locations of pine saplings in a Finnish forest, traffic accidents in Eastbourne (UK) and one week taxi movements in Beijing (China).
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Wilson, Helen Elizabeth. "Statistical analysis of replicated spatial point patterns." Thesis, Lancaster University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.268009.

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The field of pathology provides us with many opportunities for collecting replicated spatial data. Using an ordinary microscope, for example, we can digitise cell positions within windows imposed on pieces of tissue. Suppose now that we have some such replicated spatial data from several groups of individuals, where each point in each window represents a cell position. We seek to determine whether the spatial arrangement of cells differs between the groups. We propose and develop a new method which allows us to answer such questions, and apply it to some spatial neuro-anatomical data. We introduce point process theory, and extend the existing second order methods to deal with replicated spatial data. We conclude the first part of the thesis by defining Sudden Infant Death Syndrome (S.LD.S.) and Intra-Uterine Growth Retardation (LU.G.R.), and stating why these conditions are neuro-anato,mically interesting. We develop and validate a method for comparing groups of spatial data, which is motivated by analysis of variance, and uses a Monte Carlo procedure to attach significance to between-group differences. Having carried out our initial investigative work looking exclusively at the one-way set up, we extend the new methods to cope with two and higher way set ups, and again carry out some validation. We turn our attention to practical issues which arise in the collection of spatial neuroanatomical data. How, for example, should we collect the data to ensure the unbiasedness of any inference we may draw from it? We introduce the field of stereology which facilitates the unbiased sampling of tissue. We note a recent proposal to assess spatial distribution of cells using a stereological approach, and compare it with an existing second order method. We also note the level of structural heterogeneity within the brain, and consider the best way to design a sampling protocol. We conclude with a spatial analysis of cell position data, collected using our specified design, from normal birth-weight non S.LD.S., normal birth-weight S.I.D.S and low birth-weight S.LD.S cases.
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Doguwa, S. I. "Statistical analysis of mapped spatial point patterns." Thesis, University of Essex, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.383379.

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González, Monsalve Jonatan A. "Statistical tests for comparisons of spatial and spatio-temporal point patterns." Doctoral thesis, Universitat Jaume I, 2018. http://hdl.handle.net/10803/462034.

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We mainly introduce a new set of tests to compare functional descriptors in point processes context. Firstly, since the study of spatio-temporal point processes has not been widely covered in the literature, a complete review is made. The review is a reference paper of the available techniques and approaches regarding the spatio-temporal context. Secondly, a studentized permutation test is developed in the spatio-temporal case. This test is motivated by locations of tornadoes in the U.S. in a period of 36 years. Some tools have been developed as a non-separable estimator of the first-order intensity, which allows a realistic analysis of the phenomenon through the new test. Finally, a factorial two-way design is considered, where the observations are spatial point patterns in presence of replication. This methodology is motivated by a minerals engineering experiment. We develop statistics to test the influence of the factors and the possible interaction effects.
Desarrollamos un nuevo conjunto de pruebas para comparar descriptores funcionales en el contexto de procesos puntuales. Puesto que el estudio de los procesos puntuales espacio-temporales no ha sido muy exhaustivo en la literatura, hemos hecho un artículo de resumen. Introducimos un test de permutación para grupos de patrones puntuales espacio-temporales motivado por las ubicaciones de ocurrencias de tornados en EE.UU. durante 36 años. Hemos desarrollado algunas técnicas como la estimación de la intensidad de primer-orden sin suponer separabilidad, lo que permite un tratamiento más realista del fenómeno climático en sí mismo a través del nuevo test.Finalmente, hemos desarrollado algunas técnicas para el análisis de la varianza de experimentos de dos factores en presencia de réplicas cuando las observaciones son patrones puntuales espaciales. Esta metodología está motivada por un experimento de ingeniería de minerales. Desarrollamos algunos estadísticos adecuados para probar la influencia de los factores y su posible interacción.
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Pereira, Sandra M. C. "Analysis of spatial point patterns using hierarchical clustering algorithms." University of Western Australia. School of Mathematics and Statistics, 2003. http://theses.library.uwa.edu.au/adt-WU2004.0056.

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[Formulae and special characters can only be approximated here. Please see the pdf version of the abstract for an accurate reproduction.] This thesis is a new proposal for analysing spatial point patterns in spatial statistics using the outputs of popular techniques of (classical, non-spatial, multivariate) cluster analysis. The outputs of a chosen hierarchical algorithm, named fusion distances, are applied to investigate important spatial characteristics of a given point pattern. The fusion distances may be regarded as a missing link between the fields of spatial statistics and multivariate cluster analysis. Up to now, these two fields have remained rather separate because of fundamental differences in approach. It is shown that fusion distances are very good at discriminating different types of spatial point patterns. A detailed study on the power of the Monte Carlo test under the null hypothesis of Complete Spatial Randomness (the benchmark of spatial statistics) against chosen alternative models is also conducted. For instance, the test (based on the fusion distance) is very powerful for some arbitrary values of the parameters of the alternative. A new general approach is developed for analysing a given point pattern using several graphical techniques for exploratory data analysis and inference. The new strategy is applied to univariate and multivariate point patterns. A new extension of a popular strategy in spatial statistics, named the analysis of the local configuration, is also developed. This new extension uses the fusion distances, and analyses a localised neighbourhood of a given point of the point pattern. New spatial summary function and statistics, named the fusion distance function H(t), area statistic A, statistic S, and spatial Rg index, are introduced, and proven to be useful tools for identifying relevant features of spatial point patterns. In conclusion, the new methodology using the outputs of hierarchical clustering algorithms can be considered as an essential complement to the existing approaches in spatial statistics literature.
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Liu, Jie. "Exploring Ways of Identifying Outliers in Spatial Point Patterns." Digital Commons @ East Tennessee State University, 2015. https://dc.etsu.edu/etd/2528.

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This work discusses alternative methods to detect outliers in spatial point patterns. Outliers are defined based on location only and also with respect to associated variables. Throughout the thesis we discuss five case studies, three of them come from experiments with spiders and bees, and the other two are data from earthquakes in a certain region. One of the main conclusions is that when detecting outliers from the point of view of location we need to take into consideration both the degree of clustering of the events and the context of the study. When detecting outliers from the point of view of an associated variable, outliers can be identified from a global or local perspective. For global outliers, one of the main questions addressed is whether the outliers tend to be clustered or randomly distributed in the region. All the work was done using the R programming language.
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Soale, Abdul-Nasah. "Spatio-Temporal Analysis of Point Patterns." Digital Commons @ East Tennessee State University, 2016. https://dc.etsu.edu/etd/3120.

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In this thesis, the basic tools of spatial statistics and time series analysis are applied to the case study of the earthquakes in a certain geographical region and time frame. Then some of the existing methods for joint analysis of time and space are described and applied. Finally, additional research questions about the spatial-temporal distribution of the earthquakes are posed and explored using statistical plots and models. The focus in the last section is in the relationship between number of events per year and maximum magnitude and its effect on how clustered the spatial distribution is and the relationship between distances in time and space in between consecutive events as well as the distribution of the distances.
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Pranchai, Aor. "Spatial patterns and processes in a regenerating mangrove forest." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-171569.

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The global effort to rehabilitate and restore destroyed mangrove forests is unable to keep up with the high mangrove deforestation rates which exceed the average pace of global deforestation by three to five times. Our knowledge of the underlying processes of mangrove forest regeneration is too limited in order to find suitable techniques for the restoration of degraded mangrove areas. The general objective of my dissertation was to improve mangrove restoration by understanding regeneration processes and local plant-plant interaction in a regenerating Avicennia germinans forest. The study was conducted in a high-shore mangrove forest area on the Ajuruteua peninsula, State of Para, Northern Brazil. The dwarf forest consisting of shrub-like trees is recovering from a stand-replacing event caused by a road construction in 1974 which interrupted the tidal inundation of the study area. Consequently, infrequent inundation and high porewater salinity limit tree growth and canopy closure. All trees and seedlings were stem-mapped in six 20 m x 20 m plots which were located along a tree density gradient. Moreover, height, crown extent, basal stem diameter of trees were measured. The area of herbaceous ground vegetation and wood debris were mapped as well. The mapped spatial distribution of trees, seedlings and covariates was studied using point pattern analysis and point process models, such as Gibbs and Thomas point process, in order to infer underlying ecological processes, such as seed dispersal, seedling establishment, tree recruitment and tree interaction. In the first study (chapter 2), I analyzed the influence of abiotic and biotic factors on the seedling establishment and tree recruitment of A. germinans during the recolonization of severely degraded mangrove sites using point process modeling. Most seedlings established adjacent to adult trees especially under their crown cover. Moreover, seedling density was higher within patches of the herbaceous salt-marsh plants Blutaparon portulacoides and Sesuvium portulacastrum than in uncovered areas. The higher density of recruited A. germinans trees in herb patches indicated that ground vegetation did not negatively influence tree development of A. germinans. In addition, tree recruitment occurred in clusters. Coarse wood debris had no apparent effect on either life stage. These results confirm that salt-marsh vegetation acts as the starting point for mangrove recolonization and indicate that the positive interaction among trees accelerates forest regeneration. In the second study (chapter 3), I analyzed how intraspecific interaction among A. germinans trees determines their growth and size under harsh environmental conditions. Interaction among a higher number of neighboring trees was positively related to the development of a focal tree. However, tree height, internode length and basal stem diameter were only positively associated in low-density forest stands (1.2 trees m-2) and not in forest stands of higher tree density (2.7 trees m-2). These results indicated a shift from facilitation, i.e. a positive effect of tree interaction, towards a balance between facilitation and competition. In the third study (chapter 4), I used point process modeling and the individual-based model mesoFON to disentangle the impact of regeneration and interaction processes on the spatial distribution of seedlings and trees. In this infrequently inundated area, propagules of A. germinans are only dispersed at a maximum distance of 3 m from their parent tree. Furthermore, there is no evidence that the following seedling establishment is influenced by trees. I was able to differentiate positive and negative tree interactions simulated by the mangrove model mesoFON regardless of dispersal processes based on static tree size information using the mark-correlation function. The results of this dissertation suggest that mangrove forest regeneration in degraded areas is a result of facilitative and not competitive interactions among mangrove trees, seedling and herbaceous vegetation. This has important implications for the restoration of degraded mangrove forest. Degraded mangrove areas are usually restored by planting a high number of evenly spaced seedlings. However, high costs constrain this approach to small areas. Assisting natural regeneration could be a less costly alternative. Herbaceous vegetation plays a crucial role in forest recolonization by entrapping propagules and possibly ameliorating harsh environmental conditions. So far only competition among mangrove trees has been considered during restoration. However, facilitative tree interactions could be utilized by planting seedling clusters in order to assist natural regeneration instead of planting seedlings evenly-spaced over large areas. This dissertation also showed that point pattern analysis and point process modeling can enable forest ecologists to describe the spatial distribution of trees as well as to infer underlying ecological processes.
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Packard, Kevin Carew. "Modeling spatial patterns of mixed-species Appalachian forests with Gibbs point processes." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/37385.

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Stochastic point processes and associated methodology provide a means for the statistical analysis and modeling of the spatial point pattern formed from forest tree stem locations. Stochastic Gibbs point processes were explored as models that could simulate short-range clustering arising from reproduction of trees by stump sprouting, and intermediate-range inhibition of trees that may result from competition for light and growing space. This study developed and compared three pairwise interaction processes with parametric models for 2nd-order potentials and three triplets processes with models for 2nd- and 3rd-order potentials applied to a mixed-species hardwood forest in the Southern Appalachian Mountains of western North Carolina. Although the 2nd-order potentials of both the pairwise interaction and triplets processes were allowed to be purely or partially attractive, the proposed Gibbs point process models were demonstrated to be locally stable. The proposed Gibbs point processes were simulated using Markov Chain Monte Carlo (MCMC) methods; in particular, a reversible-jump Metropolis-Hastings algorithm with birth, death, and shift proposals was utilized. Parameters for the models were estimated by a Bayesian inferential procedure that utilizes MCMC methods to draw samples from the Gibbs posterior density. Two Metropolis-Hastings algorithms that do this sampling were compared; one that estimated ratios of intractable normalizing constants of the Gibbs likelihood by importance sampling and another that introduced an auxiliary variable to cancel the normalizing constants with those in the auxiliary variableâ s proposal distribution. Results from this research indicated that attractive pairwise interaction models easily degenerate into excessively clustered patterns, whereas triplets processes with attractive 2nd-order and repulsive 3rd-order interactions are more robust against excessive clustering. Bayesian inference for the proposed triplets models was found to be very computationally expensive. Slow mixing of both algorithms used for the inference combined with the long iteration times limited the practicality of the Bayesian approach. However the results obtained here indicate that triplets processes can be used to draw inference for and simulate patterns of mixed-species Appalachian hardwood forests.
Ph. D.
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Stanford, Derek C. "Fast automatic unsupervised image segmentation and curve detection in spatial point patterns /." Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/8976.

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Books on the topic "Spatial point patterns"

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Illian, Janine, Antti Penttinen, Helga Stoyan, and Dietrich Stoyan. Statistical Analysis and Modelling of Spatial Point Patterns. Chichester, UK: John Wiley & Sons, Ltd, 2007. http://dx.doi.org/10.1002/9780470725160.

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Gelfand, Alan E., and Erin M. Schliep. Bayesian Inference and Computing for Spatial Point Patterns. Beachwood, Ohio; Alexandria, Virginia: Institute of Mathematical Statistics and American Statistical Association, 2018. http://dx.doi.org/10.1214/cbms/1530065028.

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Gatrell, Anthony C. On modelling spatial point patterns in epidemiology: Cancer of the larynx in Lancashire. Lancaster: NorthWest Regional Research Laboratory, 1990.

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Boots, B. N. Point pattern analysis. Newbury Park, Calif: Sage Publications, 1988.

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Rowlingson, B. S. SPLANCS: Spatial point pattern analysis code in S-Plus. Lancaster: NorthWest Regional Research Laboratory, 1991.

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Baddeley, Adrian, Ege Rubak, and Rolf Turner. Spatial Point Patterns. Chapman and Hall/CRC, 2015. http://dx.doi.org/10.1201/b19708.

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Diggle, Peter J. Statistical Analysis of Spatial Point Patterns. 2nd ed. A Hodder Arnold Publication, 2003.

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Diggle, Peter J. Statistical Analysis of Spatial and Spatio-Temporal Point Patterns. Taylor & Francis Group, 2013.

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Diggle, Peter J. Statistical Analysis of Spatial and Spatio-Temporal Point Patterns. Chapman and Hall/CRC, 2013. http://dx.doi.org/10.1201/b15326.

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Statistical Analysis Of Spatial And Spatiotemporal Point Patterns. Taylor & Francis Inc, 2013.

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Book chapters on the topic "Spatial point patterns"

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Young, Linda J., and Jerry H. Young. "Spatial Point Patterns." In Statistical Ecology, 272–96. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-2829-3_8.

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Kaluzny, Stephen P., Silvia C. Vega, Tamre P. Cardoso, and Alice A. Shelly. "Analyzing Spatial Point Patterns." In S+SpatialStats, 146–68. New York, NY: Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4615-7826-0_6.

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Baddeley, Adrian. "Spatial Point Patterns: Models and Statistics." In Stochastic Geometry, Spatial Statistics and Random Fields, 49–114. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33305-7_3.

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Getis, Arthur, and Janet Franklin. "Second-Order Neighborhood Analysis of Mapped Point Patterns." In Perspectives on Spatial Data Analysis, 93–100. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-642-01976-0_7.

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Salmenkivi, Marko. "Efficient Mining of Correlation Patterns in Spatial Point Data." In Lecture Notes in Computer Science, 359–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11871637_35.

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Coeurjolly, Jean-François, and Frédéric Lavancier. "Understanding Spatial Point Patterns Through Intensity and Conditional Intensities." In Stochastic Geometry, 45–85. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13547-8_2.

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Getis, Arthur. "Second-Order Analysis of Point Patterns: The Case of Chicago as a Multi-center Urban Region." In Perspectives on Spatial Data Analysis, 83–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-642-01976-0_6.

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Robertson, Colin, and Steven Roberts. "Bivariate Spatial Clustering Analysis of Point Patterns: A Graph-Based Approach." In Lecture Notes in Computer Science, 403–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39649-6_29.

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D’Angelo, Nicoletta, Mauro Ferrante, Antonino Abbruzzo, and Giada Adelfio. "Determinants of spatial intensity of stop locations on cruise passengers tracking data." In Proceedings e report, 159–64. Florence: Firenze University Press, 2021. http://dx.doi.org/10.36253/978-88-5518-304-8.31.

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This paper aims at analyzing the spatial intensity in the distribution of stop locations of cruise passengers during their visit at the destination through a stochastic point process modelling approach on a linear network. Data collected through the integration of GPS tracking technology and questionnaire-based survey on cruise passengers visiting the city of Palermo are used, to identify the main determinants which characterize their stop locations pattern. The spatial intensity of stop locations is estimated through a Gibbs point process model, taking into account for both individual-related variables, contextual-level information, and for spatial interaction among stop points. The Berman-Turner device for maximum pseudolikelihood is considered, by using a quadrature scheme generated on the network. The approach used allows taking into account the linear network determined by the street configuration of the destination under analysis. The results show an influence of both socio-demographic and trip-related characteristics on the stop location patterns, as well as the relevance of distance from the main attractions, and potential interactions among cruise passengers in stop configuration. The proposed approach represents both improvements from the methodological perspective, related to the modelling of spatial point process on a linear network, and from the applied perspective, given that better knowledge of the determinants of spatial intensity of visitors’ stop locations in urban contexts may orient destination management policy.
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Hamstead, Zoé A., and Jason Sauer. "Mapping Vulnerability to Weather Extremes: Heat and Flood Assessment Approaches." In Resilient Urban Futures, 47–66. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63131-4_4.

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AbstractAssessing present social and biophysical conditions of communities that are at risk of injury due to extreme weather events is an important component of creating future visions of resilience. Spatial patterns of vulnerability to extreme events are manifestations of structural injustice that leave their mark on the built environment and in socio-spatial segregation patterns. Socio-spatial inequity often arises from development practices that favor particular racial and ethnic social groups over others. These segregation patterns are aligned with patterns of exposure to pollution, extreme weather events, and other types of environmental hazards. Spatial vulnerability assessments can be powerful tools for prioritizing where and how cities should make investments for mitigating the impacts of extreme events, and can provide an entry point for asking more fundamental questions about the processes that produce patterns of climate inequity, as well as how to avoid reproducing such processes in the future. Maps express uneven distributions of risk and manifestations of structural inequality in social–ecological–technological systems (SETS). They enable communities to visualize distributional injustice, consider ways in distributions that may be misaligned with cultural values, and develop adaptive practices toward climate justice. Here, we demonstrate approaches for assessing vulnerability to extreme flooding and heat, and show how vulnerability distributions are embedded in landscape patterns that produce uneven risk.
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Conference papers on the topic "Spatial point patterns"

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"The impact of spatial scales on discretised spatial point patterns." In 20th International Congress on Modelling and Simulation (MODSIM2013). Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2013. http://dx.doi.org/10.36334/modsim.2013.i4.kang.

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Burguet, Jasmine, Philippe Mailly, and Philippe Andrey. "Statistical groupwise comparison of spatial point patterns in biological imaging." In 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013). IEEE, 2013. http://dx.doi.org/10.1109/isbi.2013.6556510.

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Skolnick, Michael M., and Peter Marineau. "Pebble_Pond: a morphological wave propagation algorithm for representing spatial point patterns." In San Diego '92, edited by Paul D. Gader, Edward R. Dougherty, and Jean C. Serra. SPIE, 1992. http://dx.doi.org/10.1117/12.60654.

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Kirchner, Thomas R., Donna Vallone, Jennifer Cantrell, Andrew Anesetti-Rothermel, Jennifer Pearson, Sarah Cha, Jennifer Kreslake, Ollie Ganz, Michael Tacelosky, and David Abrams. "Individual mobility patterns and real-time geo-spatial exposure to point-of-sale tobacco marketing." In the conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2448096.2448104.

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Boyacioglu, Kadir Faruk, and Dogu Arifler. "Second-Order Analysis of Formation of Holes in Spatial Point Patterns: Applications in Wireless Sensor Networks." In 2007 5th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt). IEEE, 2007. http://dx.doi.org/10.1109/wiopt.2007.4480074.

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Peng, Tao, and Satyandra K. Gupta. "Algorithms for Generating Adaptive Projection Patterns for 3-D Shape Measurement." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-35452.

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Point cloud acquisition using digital fringe projection (PCCDFP) is a non-contact technique for acquiring dense point clouds to represent the 3-D shapes of objects. Most existing PCCDFP systems use projection patterns consisting of straight fringes with fixed fringe pitches. In certain situations, such patterns do not give the best results. In our earlier work, we have shown that in some situations, patterns that use curved fringes with spatial pitch variation can significantly improve the process of constructing point clouds. This paper describes algorithms for automatically generating adaptive projection patterns that use curved fringes with spatial pitch variation to provide improved results for an object being measured. In addition, we also describe the supporting algorithms that are needed for utilizing adaptive projection patterns. Both simulation and physical experiments show that, adaptive patterns are able to achieve improved performance, in terms of measurement accuracy and coverage, than fixed-pitch straight fringe patterns.
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Rivera-López, Bárbara, and Manuel Matas Luci. "Spatial Reference Patterns as a Point of Hegemonic Struggle: A Case Study of Biotechnology Journals in Latin America." In 22nd International Conference on Electronic Publishing. OpenEdition Press, 2018. http://dx.doi.org/10.4000/proceedings.elpub.2018.5.

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Sun, Xiaochuan, and Shahram Payandeh. "Estimation of Incision Patterns Based on Visual Tracking of Surgical Tools in Minimally Invasive Surgery." In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-37827.

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In minimally invasive surgery, the positions of surgical tools are important in multiple instruments set-up and procedures. Typically, each surgery requires 4–5 incision holes and for each specific procedure, the layout of points defines specific pattern. Taking advantage of this possible one-to-one relationship between a specific procedure in minimally invasive surgery and the incision patterns, such patterns can be utilized in tele-monitoring of trainee during an emulated surgical operation. For example, in performance evaluation of trainee, this procedure would automatically estimate and verify the initial incision pattern to that of the predefined expected template associated with a particular surgical procedure. In this paper, we propose and analyze two models, based on color and shape respectively, to reconstruct the pattern. Both approaches use image information only to reconstruct the incision patterns in three dimensional space. The challenge of monocular endoscopic view is the lack of depth perception which hindered the vision-based tracking of laparoscopic tools. To address the problem, we present a method to determine not only the spatial tip position of the surgical tools, but also their orientation with respect to the camera coordinate frame. Detailed formulation shows that how segmented tool edges and camera field of view localize the 3D orientations of tools. Then, 3D position of the tool tip is reconstructed using either color or edge detection method. Finally, the orientations and the position of tool tips uniquely determine the poses of the tools. From above procedures, geometrical models of cylindrical tools can be constructed in each sequence of mono-camera images. To further use the tracking result in order to localize the incision point, we computed the vectors of the cylindrical tool center lines at multiple poses at number of frames. Extracted incision point is further analyzed as a recognition pattern to map into the patients’ pre-operative incision procedure. Accuracy of 3D tool pose estimation and incision pattern is evaluated in real image sequences with known ground truth.
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Jenness, Nathan J., Daniel G. Cole, and Robert L. Clark. "Three-Dimensional Holographic Lithography Using a Spatial Light Modulator." In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-50067.

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In this paper we present a lithographic process with the ability to automatically translate and arbitrarily position three-dimensional (3D) computer-generated patterns through the use of phase holograms. This method, dynamic maskless holographic lithography (DMHL), advances current photo-directed patterning and functionalization capabilities by expanding the capability to manipulate light in real-time without the use of expensive fixed masks. The system could be used for large-scale parallel manufacturing over larger areas and for point specific serial fabrication, interrogation, and metrology. The use of coherent illumination allows for the direct creation of 3D patterns of light for lithography as opposed to the mechanical stage, layer-by-layer 3D fabrication approach typical of direct-write systems. Extrinsic control over interfacial properties will provide a method for addressing aqueous phase bionanotechnolgy experimental systems in which detection, separation, transport, and handling are vital.
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Zhang, Lu, Zhu Sun, Jie Zhang, Yu Lei, Chen Li, Ziqing Wu, Horst Kloeden, and Felix Klanner. "An Interactive Multi-Task Learning Framework for Next POI Recommendation with Uncertain Check-ins." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/491.

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Studies on next point-of-interest (POI) recommendation mainly seek to learn users' transition patterns with certain historical check-ins. However, in reality, users' movements are typically uncertain (i.e., fuzzy and incomplete) where most existing methods suffer from the transition pattern vanishing issue. To ease this issue, we propose a novel interactive multi-task learning (iMTL) framework to better exploit the interplay between activity and location preference. Specifically, iMTL introduces: (1) temporal-aware activity encoder equipped with fuzzy characterization over uncertain check-ins to unveil the latent activity transition patterns; (2) spatial-aware location preference encoder to capture the latent location transition patterns; and (3) task-specific decoder to make use of the learned latent transition patterns and enhance both activity and location prediction tasks in an interactive manner. Extensive experiments on three real-world datasets show the superiority of iMTL.
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Reports on the topic "Spatial point patterns"

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Collins, Clarence O., and Tyler J. Hesser. altWIZ : A System for Satellite Radar Altimeter Evaluation of Modeled Wave Heights. Engineer Research and Development Center (U.S.), February 2021. http://dx.doi.org/10.21079/11681/39699.

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This Coastal and Hydraulics Engineering Technical Note (CHETN) describes the design and implementation of a wave model evaluation system, altWIZ, which uses wave height observations from operational satellite radar altimeters. The altWIZ system utilizes two recently released altimeter databases: Ribal and Young (2019) and European Space Agency Sea State Climate Change Initiative v.1.1 level 2 (Dodet et al. 2020). The system facilitates model evaluation against 1 Hz1 altimeter data or a product created by averaging altimeter data in space and time around model grid points. The system allows, for the first time, quantitative analysis of spatial model errors within the U.S. Army Corps of Engineers (USACE) Wave Information Study (WIS) 30+ year hindcast for coastal United States. The system is demonstrated on the WIS 2017 Atlantic hindcast, using a 1/2° basin scale grid and a 1/4° regional grid of the East Coast. Consistent spatial patterns of increased bias and root-mean-square-error are exposed. Seasonal strengthening and weakening of these spatial patterns are found, related to the seasonal variation of wave energy. Some model errors correspond to areas known for high currents, and thus wave-current interaction. In conjunction with the model comparison, additional functions for pairing altimeter measurements with buoy data and storm tracks have been built. Appendices give information on the code access (Appendix I), organization and files (Appendix II), example usage (Appendix III), and demonstrating options (Appendix IV).
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