Relevant bibliographies by topics / Spatial analysis (Statistics) Geography

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

Academic literature on the topic 'Spatial analysis (Statistics) Geography'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "Spatial analysis (Statistics) Geography"

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Páez. "Spatial statistics for urban analysis: A review of techniques with examples." GeoJournal 61, no. 1 (2005): 53. http://dx.doi.org/10.1007/sgejo-004-0877-x.

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Ceccato, Vânia, Robert Haining, and Paola Signoretta. "Exploring Offence Statistics in Stockholm City Using Spatial Analysis Tools." Annals of the Association of American Geographers 92, no. 1 (March 2002): 29–51. http://dx.doi.org/10.1111/1467-8306.00278.

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Coulston, John W., and Kurt H. Riitters. "Geographic Analysis of Forest Health Indicators Using Spatial Scan Statistics." Environmental Management 31, no. 6 (June 1, 2003): 764–73. http://dx.doi.org/10.1007/s00267-002-0023-9.

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Rosenberg, Michael S., and Corey Devin Anderson. "PASSaGE: Pattern Analysis, Spatial Statistics and Geographic Exegesis. Version 2." Methods in Ecology and Evolution 2, no. 3 (December 15, 2010): 229–32. http://dx.doi.org/10.1111/j.2041-210x.2010.00081.x.

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Leung, Yee, Chang-Lin Mei, and Wen-Xiu Zhang. "Statistical Test for Local Patterns of Spatial Association." Environment and Planning A: Economy and Space 35, no. 4 (April 2003): 725–44. http://dx.doi.org/10.1068/a3550.

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In recent years, there has been a growing interest in the use of local measures such as Anselin's LISAs and Ord and Getis G statistics to identify local patterns of spatial association. The statistical significance test based on local statistics is one of the most important aspects in performing this kind of analysis, and a randomized permutation approach and normal approximation are commonly used to derive the p-values of the statistics. To circumvent some of the shortcomings of these existing methods and to offer a more formal approach in line with classical statistical framework, we develop in this paper an exact method for computing the p-values of the local Moran's Ii, local Geary's ci, and the modified Ord and Getis G statistics based on the distributional theory of quadratic forms in normal variables. Furthermore, an approximate method, called three-moment χ2 approximation, with explicit calculation formulae is also proposed to achieve a computational cost lower than the exact method. Numerical evaluation on the accuracy of the approximate null distributions of the local statistics demonstrates that the proposed three-moment χ2 method is useful in some situations although it is inappropriate for approximating the null distribution of Ii. The study not only provides an exact test for local patterns of spatial association, but also put the tests of several local statistics within a unified statistical framework.
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Кандрычын and S. Kandrychyn. "Geography of ascariasis in Belarus: cultural and anthropological issues (Part 1)." Russian Journal of Parasitology 3, no. 3 (September 25, 2016): 337–44. http://dx.doi.org/10.12737/21658.

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Objective of research: The analysis of spatial distribution of ascariasis among the population in different regions of the republic of Belarus with respect to anthropological and cultural aspects. Investigations for regional differences in ascariasis conducted in the USSR were focused rather on climatic, hygienic and economic factors and didn’t consider the causative role of cultural and anthropological factors in epidemiological process. The study is aimed at correlation of regional indices of ascariasis with the previously defined spatial historical gradient manifested in Belarus. Materials and methods: The effect of social and cultural spatial gradient was assessed by comparison of difference in ascariasis morbidity between eastern and western regions of Belarus. Thus, the effect of ethnic and anthropological spatial gradient was considered in comparison of epidemiological indices between the Brest region (south-western part of Belarus) and Vitebsk region (north-eastern part). The analysis was conducted with the historical perspective; the regional epidemiological statistics were provided for two periods 1970-1989 and 2000-2014. Regional statistical materials of the republic of Belarus presented in the annual reports of the national Ministry of Health were used as an empirical basis. Results and discussion: The analysis showed, that the differentiation trend in distribution of ascariasis in Belarus correlates both with historical-cultural and anthropological spatial gradients. The identified pattern of regional differentiation allows to evaluate the complex effect of sociocultural and anthropogenic components on epidemiological features of ascariasis.
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Hepple, Leslie W. "Multiple Regression and Spatial Policy Analysis: George Udny Yule and the Origins of Statistical Social Science." Environment and Planning D: Society and Space 19, no. 4 (August 2001): 385–407. http://dx.doi.org/10.1068/d291.

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Studies on the history of statistics by MacKenzie and on quantitative geography by Barnes have suggested that the lineaments and assumptions of statistical methods such as correlation and regression are closely related to their origin in biometrics and eugenics. This paper challenges that view by examining in detail the work of George Udny Yule. Yule was a colleague of Karl Pearson in the 1890s, but was interested in social science and social policy applications, not eugenics. In the late 1890s he constructed both the theory and application of multiple regression analysis, using geographical data. The paper examines Yule's work and its context, relating it to debates on the history of statistics, and traces the subsequent early diffusion of regression and correlation into the social sciences. The paper concludes by arguing for greater recognition of Yule's pivotal role, and also for further studies on the history of quantitative social science.
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Ingram, Matthew C., and Imke Harbers. "Spatial Tools for Case Selection: Using LISA Statistics to Design Mixed-Methods Research." Political Science Research and Methods 8, no. 4 (May 6, 2019): 747–63. http://dx.doi.org/10.1017/psrm.2019.3.

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AbstractMixed-methods designs, especially those in which case selection is regression-based, have become popular across the social sciences. In this paper, we highlight why tools from spatial analysis—which have largely been overlooked in the mixed-methods literature—can be used for case selection and be particularly fruitful for theory development. We discuss two tools for integrating quantitative and qualitative analysis: (1) spatial autocorrelation in the outcome of interest; and (2) spatial autocorrelation in the residuals of a regression model. The case selection strategies presented here enable scholars to systematically use geography to learn more about their data and select cases that help identify scope conditions, evaluate the appropriate unit or level of analysis, examine causal mechanisms, and uncover previously omitted variables.
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Griffith, Daniel A. "A Spatial Analysis of Selected Art: a GIScience-Humanities Interface." International Journal of Humanities and Arts Computing 14, no. 1-2 (March 2020): 154–75. http://dx.doi.org/10.3366/ijhac.2020.0250.

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This exposition presents little-known connections between geography, through geographic information systems (GISs), mathematics, through matrix algebra, and art, through paintings and images, adding to the geo-humanities, spatial humanities, and humanistic mathematics literature. To this end, findings summarized for spatial statistical analyses of selected Susie Rosmarin paintings (which are reminiscent of visualizations of certain mathematical quantities known as eigenvectors), remotely sensed images that have appeared in art exhibits, and selected famous paintings by historically renowned artists reveal that spatial autocorrelation constitutes a fundamental element of art. These analyses extend the tradition of visualizing fractals as art, and interfacing cartography with art. This paper promotes analytical art, and establishes additional commonalities for GIScience, mathematics, and art.
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Kim, Minho. "Linked Micromap: Exploratory Data Analysis and Geographic Visualization of Spatial Statistics Data." Journal of the Korean Cartographic Association 15, no. 2 (August 30, 2015): 39–50. http://dx.doi.org/10.16879/jkca.2015.15.2.039.

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Dissertations / Theses on the topic "Spatial analysis (Statistics) Geography"

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AvRuskin, Gillian. "Towards A Spatial Model of Rurality." Fogler Library, University of Maine, 2000. http://www.library.umaine.edu/theses/pdf/AvRuskinG2000.pdf.

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Jensen, Daniel. "Spatial analysis and visualization in the NBA using GIS applications." Thesis, California State University, Long Beach, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1527009.

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Basketball is a unique sport in which the use of space and time is greatly important for a team’s success. Furthermore, the National Basketball Association (NBA) is undergoing drastic change in terms of the way teams approach spatial issues as well as the spatio-temporal technologies and analytics. Given these facts, Geographic Information Systems (GIS) provide the opportunity to develop new analytic and visual methodologies to perform spatial analysis for team performances and meet the league’s changing needs. This project thus develops new approaches, methods, and toolsets using GIS to demonstrate its efficacy and potential for professional application in the NBA. The first application uses GIS to adapt Relative Motion analysis techniques to an existing play, seeking to represent the average motion characteristics entailed therein. The other application uses a tool developed to map, glean spatial statistics, and model the use and importance of floor spacing for teams in the NBA.

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Kim, Kamyoung. "Spatial analytical approaches for supporting security monitoring." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1186593136.

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Wheeler, David C. "Diagnostic tools and remedial methods for collinearity in linear regression models with spatially varying coefficients." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1155413322.

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Manley, David John. "The modifiable areal unit phenomenon : an investigation into the scale effect using UK census data /." St Andrews, 2006. http://hdl.handle.net/10023/465.

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Wang, Ninghua Nathan. "Statistics for Time-Series Spatial Data| Applying Survival Analysis to Study Land-Use Change." Thesis, University of California, Santa Barbara, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3612050.

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Traditional spatial analysis and data mining methods fall short of extracting temporal information from data. This inability makes their use difficult to study changes and the associated mechanisms of many geographic phenomena of interest, for example, land-use. On the other hand, the growing availability of land-change data over multiple time intervals and longer time frames, often based on satellite imagery, presents to land-change study a great opportunity, given that this information can be effectively utilized. This methodological gap highlights the need to better understand the analytical challenges brought by temporal complexities, and to investigate alternative analytical frameworks that could handle those challenges.

This dissertation attempted to achieve three goals: 1) finding metrics to capture temporal trends, 2) dealing with temporally imprecise data due to constraints of frequency, duration, and starting time of data collection, and 3) handling variables with time-changing values. A simulated land-change dataset based on an agent-based model of residential development and an empirical dataset from two case study sites in San Diego and Tijuana were used for this investigation.

Results from the simulation dataset indicated that the survival function and the hazard function are important metrics to reveal temporal trends. In general the results of land-change analysis are sensitive to time frequency, in particular when time-dependent variables are also present. Longer duration benefits land-change analysis since longer durations contains more information. However, time-dependent variables with measures over a long period are more difficult for detection, which may pose a challenge. Starting time also affects the analytical results because the level of process uncertainty varies at different starting times. Findings from real world data mostly agree with those from computational data. Time dependent variables present a major challenge in land-change analysis, and survival analysis can better handle time-independent variables and thus better forecast urban growth.

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Harvey, Rachel. "Eliciting and mapping the attributes of landscape perception : an integration of personal construct theory (PCT) with geographic information systems (GIS)." Thesis, Heriot-Watt University, 1995. http://hdl.handle.net/1842/10322.

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Scotland's tourist industry partly depends upon the quality of the Scottish landscape. However, despite demands for improved management of landscape resources, there is no standard method for the assessing landscape quality. This research takes a user-based approach to this problem and explores the use of Kelly's Personal Construct Theory (PCT) in eliciting underpinning attributes and dimensions of perception in a range of uses and across a range of Scottish landscapes. A novel aspect of the research is that it involves experimentation in mapping the resultant constructs through use of a Geographic Information System (GIS). Sixteen key constructs were gained from one to one. interviews and used in the preliminary mapping experiments. These showed that it was possible to express the constructs spatially. To evaluate between user group/landscape type responses a questionnaire was designed, piloted and applied. A total of 1286 responses were analyzed. Differences were found between landscape type but were stronger between user groups. The research has demonstrated that the application of PCT coupled to GIS is a valuable way of exploring landscape perception/landscape quality and their spatial expression.
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Chen, Yan. "Spatial Analysis of Fatal Automobile Crashes in Nashville, TN, 2001-2011." TopSCHOLAR®, 2013. http://digitalcommons.wku.edu/theses/1300.

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With increasing levels of motor vehicle ownership, automobile crashes have become a serious public issue in the U.S. and around the world. Knowing when, where, and how traffic accidents happen is critical in order to ensure road safety and to plan for adequate road infrastructure. There is a rich body of literature pertaining to time-related fatal crashes, most of which focuses on non-spatial factors such as a driver’s visibility at night, drinking and drug use, and road conditions. These studies provide a theoretical basis for understanding the causes of crashes from a non-spatial perspective, and a number of traffic laws and policies consequently have been enacted to minimize the impacts of non-spatial factors. Over the past few years, advances in Geographic Information Systems (GIS) have greatly enhanced our ability to analyze traffic accidents from a spatial perspective. This study aims to fill a void in traffic safety studies by comparing and analyzing the differences in the spatial distribution of fatal crashes based on temporal factors, specifically in three periods: 1) day and night; 2) A.M. rush hours and P.M. rush hours; and 3) weekdays and weekends. With the Nashville Metropolitan Area as the study area, the research utilized a number of spatial point-pattern analysis (SPPA) methods, including planar KDE, planar global auto K function, network global cross K functions, and network local cross K functions. All fatal crashes in the Nashville area were found to be clustered and generally follow the patterns of average daily traffic flow. All time-based subtypes of fatal crashes also were found to be concentrated within the central urban area of Nashville, mostly along major roads, and especially near major road intersections and highway interchanges. No notable spatial differences were detected among the subtypes of fatal crashes when applying network global cross K function. However, with the help of the network local cross K function, some localized spatial differences were identified. Some specific locations of hotspots of nighttime and P.M. rush hour fatal crashes were found not to be at the same locations as those at of daytime and A.M. rush hour fatal crashes, respectively. The approach adopted in this study not only provides a new way to analyze spatial distribution of spatial point events such as fatal crashes, but it also can be applied readily to real-world applications. A good understanding of where these spatial differences are should help various agencies practice effective measures and policies in order to improve road conditions, reduce traffic accidents, and ensure road safety.
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Kordi, Maryam. "Geographically weighted spatial interaction (GWSI)." Thesis, University of St Andrews, 2013. http://hdl.handle.net/10023/4112.

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One of the key concerns in spatial analysis and modelling is to study and analyse similarities or dissimilarities between places over geographical space. However, ”global“ spatial models may fail to identify spatial variations of relationships (spatial heterogeneity) by assuming spatial stationarity of relationships. In many real-life situations spatial variation in relationships possibly exists and the assumption of global stationarity might be highly unrealistic leading to ignorance of a large amount of spatial information. In contrast, local spatial models emphasise differences or dissimilarity over space and focus on identifying spatial variations in relationships. These models allow the parameters of models to vary locally and can provide more useful information on the processes generating the data in different parts of the study area. In this study, a framework for localising spatial interaction models, based on geographically weighted (GW) techniques, has been developed. This framework can help in detecting, visualising and analysing spatial heterogeneity in spatial interaction systems. In order to apply the GW concept to spatial interaction models, we investigate several approaches differing mainly in the way calibration points (flows) are defined and spatial separation (distance) between flows is calculated. As a result, a series of localised geographically weighted spatial interaction (GWSI) models are developed. Using custom-built algorithms and computer code, we apply the GWSI models to a journey-to-work dataset in Switzerland for validation and comparison with the related global models. The results of the model calibrations are visualised using a series of conventional and flow maps along with some matrix visualisations. The comparison of the results indicates that in most cases local GWSI models exhibit an improvement over the global models both in providing more useful local information and also in model performance and goodness-of-fit.
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Oris, William Nathan. "Spatial Analysis of Fatal Automobile Crashes in Kentucky." TopSCHOLAR®, 2011. http://digitalcommons.wku.edu/theses/1119.

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Fatal automobile crashes have claimed the lives of over 33,000 people each year in the United States since 1995. As in any point event, fatal crash events do not occur randomly in time or space. The objectives of this study were to identify spatial patterns and hot spots in FARS (Fatal Analysis Reporting System) fatal crash events based on temporal and demographic characteristics. The methods employed included 1) rate calculation using FARS points and average daily traffic flow; 2) planar kernel density estimation of FARS crash events based on temporal and demographic attributes within the data; and 3) two case studies using network kernel density estimation along roadways to determine hot spots fatal crashes in Jefferson County and Warren County. Rate calculation analyses revealed that travel on roads with high speed limits and winding topography led to the highest number of crashes and highest rate of fatal crashesper 1,000 daily vehicles. Planar kernel density estimation results showed temporalpatterns, revealing that ‘hot spots’ and fatalities were highest in the summer, and typically occurred from 2pm-6pm on the weekends. Further, the 16 to 25 year age group was responsible for the most significant ‘hot spots’ and the most fatal accidents. Also showing that the most significant hot spots involving alcohol occurring in close proximity to meeting places such as bars and restaurants. Finally, results from the network kernel density estimation revealed that most hot spots were in high traffic areas of where majorr oads converged with secondary roads.
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Books on the topic "Spatial analysis (Statistics) Geography"

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Spatial autocorrelation. Norwich: Geo Books, 1986.

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Spatial autocorrelation. Newbury Park, Calif: Sage Publications, 1988.

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Chris, Brunsdon, and Charlton Martin, eds. Quantitative geography: Perspectives on spatial data analysis. London: Sage Publications, 2000.

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Sibley, David. Spatial applications of exploratory data analysis. Norwich: Geo Books, 1988.

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G, Amrhein Carl, and Desloges Joseph R, eds. Statistical analysis for geographers. Englewood Cliffs, N.J: Prentice Hall, 1991.

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Spatial autocorrelation: A primer. Washington, D.C: Association of American Geographers, 1987.

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J, Layne Larry, Ord J. K, and Sone Akio, eds. A casebook for spatial statistical data analysis: A compilation of analyses of different thematic data sets. New York: Oxford University Press, 1999.

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Shen, Jianfa. Dynamic analysis of spatial population systems. Norwich, England: School of Environmental Sciences, University of East Anglia, 1994.

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John), Unwin D. (David, ed. Geographic information analysis. 2nd ed. Hoboken, N.J: John Wiley & Sons, 2010.

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O'Sullivan, David. Geographic information analysis. 2nd ed. Hoboken, N.J: J. Wiley & Sons, 2010.

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Book chapters on the topic "Spatial analysis (Statistics) Geography"

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Anselin, Luc, and Arthur Getis. "Spatial Statistical Analysis and Geographic Information Systems." In Perspectives on Spatial Data Analysis, 35–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-642-01976-0_3.

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Tong, Xiaohua, Huan Xie, Shijie Liu, Yanmin Jin, Wenzhong Shi, Jinfeng Wang, Tao Pei, Yong Ge, and Changqing Zhu. "Uncertainty of Spatial Information and Spatial Analysis." In Springer Geography, 511–22. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1884-8_25.

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Pei, Tao, Jun Xu, Jianhua Gong, Xiaoping Liu, Jianghao Wang, Shihong Du, Chengzhi Qin, Lin Yang, and You Wan. "Spatial Analysis and Simulation." In Springer Geography, 339–66. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1884-8_15.

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Linke, Andrew M., and John O'Loughlin. "Spatial Analysis." In The Wiley Blackwell Companion to Political Geography, 187–205. Chichester, UK: John Wiley & Sons, Ltd, 2015. http://dx.doi.org/10.1002/9781118725771.ch15.

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Anselin, Luc, and Arthur Getis. "Spatial statistical analysis and geographic information systems." In Geographic Information Systems, Spatial Modelling and Policy Evaluation, 35–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-77500-0_3.

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Oliveira, Victor, and A. Alexandre Trindade. "Spatial Statistics." In Encyclopedia of Social Network Analysis and Mining, 1976–90. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-6170-8_167.

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Oliveira, Victor, and A. Alexandre Trindade. "Spatial Statistics." In Encyclopedia of Social Network Analysis and Mining, 2882–95. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7131-2_167.

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Oliveira, Victor, and A. Alexandre Trindade. "Spatial Statistics." In Encyclopedia of Social Network Analysis and Mining, 1–15. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4614-7163-9_167-1.

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Fox, Charles. "Spatial Analysis." In Springer Textbooks in Earth Sciences, Geography and Environment, 107–23. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72953-4_8.

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Streit, Ulrich. "Statistical Analysis of Spatial Data in Geographic Information Systems." In Data Analysis and Information Systems, 208–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-642-80098-6_18.

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Conference papers on the topic "Spatial analysis (Statistics) Geography"

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Ye, Ling, and Jianhua Mao. "Spatial analysis on SQL Geography and Geometry data." In 2010 International Conference on Audio, Language and Image Processing (ICALIP). IEEE, 2010. http://dx.doi.org/10.1109/icalip.2010.5685200.

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Chen, Rongguo, and Siqing Chen. "Statistics analysis embedded in spatial DBMS." In Geoinformatics 2006: Geospatial Information Technology, edited by Huayi Wu and Qing Zhu. SPIE, 2006. http://dx.doi.org/10.1117/12.712952.

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Shu, Hong, Chao Zhao, and Aiping Xu. "Spatio-temporal statistics for exploratory NDVI image analysis." In International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, edited by Yaolin Liu and Xinming Tang. SPIE, 2009. http://dx.doi.org/10.1117/12.838576.

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Mujiono, Mujiono, Tito Latif Indra, and Djoko Harmantyo. "Spatial Analysis of Deforestation and Its Impact on Carbon Emissions Using FREL." In lst International Cohference on Geography and Education (ICGE 2016). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/icge-16.2017.55.

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Bhattacharya, Prosun, Julian Ijumulana, and Felix Mtalo. "SPATIAL STATISTICS: A TOOL FOR SPATIAL ANALYSIS OF GEOCONTAMINANTS IN GROUNDWATER." In GSA Annual Meeting in Seattle, Washington, USA - 2017. Geological Society of America, 2017. http://dx.doi.org/10.1130/abs/2017am-307971.

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Burgess, Arthur E. "Mammographic structure: data preparation and spatial statistics analysis." In Medical Imaging '99, edited by Kenneth M. Hanson. SPIE, 1999. http://dx.doi.org/10.1117/12.348620.

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CAKMAK, SABIT, RICK BURNETT, MICHAEL JERRETT, MARK S. GOLDBERG, ARDEN POPE, RENJUN MA, and DANIEL KREWSKI. "SPATIAL ASSOCIATION BETWEEN COMMUNITY AIR POLLUTION AND HEART DISEASE: ANALYSIS OF CORRELATED DATA." In Proceedings of Statistics 2001 Canada: The 4th Conference in Applied Statistics. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2002. http://dx.doi.org/10.1142/9781860949531_0007.

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Sambah, Abu Bakar, Feni Iranawati, Syarifah H Julindasari, Dian Pranoto, Ledhyane Ika Harlyan, and Ahmad Fauzan Ghafiky. "The Spatial Analysis in Tuna Habitat Related to The Ocean Variability in The Indian Ocean." In lst International Cohference on Geography and Education (ICGE 2016). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/icge-16.2017.51.

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Liu, Guifang, and Heli Lu. "Statistics analysis on SPOT 5 classification accuracy of different data fusion methods." In International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, edited by Yaolin Liu and Xinming Tang. SPIE, 2009. http://dx.doi.org/10.1117/12.838450.

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Sumiyati, Sri. "Analysis of Examination Location with Spatial Approach (Study in UPBJJ-UT Lampung, Surakarta, Makassar and Banjarmasin in Universitas Terbuka)." In lst International Cohference on Geography and Education (ICGE 2016). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/icge-16.2017.45.

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