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| 1: | Spatial Statistics Toolbox 1.1 HTML Documentation Spatial Statistics Toolbox 1.1 By R. Kelley Pace LREC Endowed Chair of Real Estate E.J. Ourso College of Business Administration Louisiana State University Baton Rouge, LA 70803-6308 (225)-388-6256 FAX: (225)-334-1227 kelley@spatial-statistics.com kelley@pace.am www.spatial-statistics.com and Ronald Barry Associate Professor of Statistics Department of Mathematical Sciences University of Alaska Fairbanks, Alaska 99775-6660 (907)-474-7226 FAX: (907)-474-5394 FFRPB@uaf.edu The authors gratefully acknowledge the research support they have received from the University of Alaska and Louisiana State University. We also wish to acknowledge support from the Center for Real Estate and Urban Studies at the University of Connecticut at Storrs. We would like to thank Jennifer Loftin for her editorial assistance as well as Rui Li, Sean McDonald, Robby Singh, and Dek Terrell for having made sure that the Toolbox could run on machines other than my own. Spatial Statistics Toolbox I. ... http://www.spatial-statistics.com/... ml/space_tools_v11.html |
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| 2: | Managing spatial components of enterprise data URISA (1994), p231-244, copyright Urban and Regional Information Association Trevor R. Hanson Hanson-Smith, Ltd. 617A Fan Hill Road Monroe, Connecticut 06468 (203) 452-1500; in Chicago: (312) 902-4785 MANAGING SPATIAL COMPONENTS OF ENTERPRISE DATA Abstract: In the overall IS environment, geographic and spatial processing have been orphans. Despite successes with specialized, single-seat workstation applications for planning and analysis, mainstream computing has tended to ignore spatial data. For example, corporate data about customers or facilities have generally been available to GIS environments through their unique identifiers - not via spatial predicates. Only specialized analysis tools have been able to answer spatial questions: "What parcels/mains/people are near this street/outfall/project?" It would be impractical to install spatial analysis software on every computer platform. On the other hand, infrastructure facilities, area boundaries, and other real-world ... http://spatialodyssey.ursus.maine.edu/... /urisa/ur94021.html |
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| 3: | SPATIAL ANALYSIS IN A GIS ENVIRONMENT SPATIAL ANALYSIS IN A GIS ENVIRONMENT Objectives The purpose of this paper is to identify a variety of methods, techniques, and approaches for the analysis of spatial and time-space data and models, utilizing the ability of geographic information systems (GISs) to store, select, manipulate, explore, analyze, and display georeferenced data. Background Problems of human health, social deprivation, global and local environmental change, industrial and economic development, and a host of other problems demand that we make sense of what is happening in the world around us. The term "spatial analysis" encompasses a wide range of techniques for analyzing, computing, visualizing, simplifying, and theorizing about geographic data. Methods of spatial analysis can be as simple as taking measurements from a map or as sophisticated as complex geocomputational procedures based on numerical analysis. At the same time that we are being flooded by the benefits of new technologies for ... http://www.ucgis.org/research_white/anal.html |
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| 4: | Spatial Statistics and Real Estate Spatial Statistics and Real Estate By R. Kelley Pace LREC Chair of Real Estate Department of Finance E.J. Ourso College of Business Administration Louisiana State University Baton Rouge, LA 70803 (225)-388-6256 FAX: (225)-388-6366 kelley@spatial-statistics.com kelley@pace.am Ronald Barry Associate Professor of Statistics Department of Mathematical Sciences University of Alaska Fairbanks, Alaska 99775-6660 (907)-474-7226 FAX: (907)-474-5394 FFRPB@uaf.edu C.F. Sirmans Director, Center for Real Estate and Urban Economic Studies University of Connecticut 368 Fairfield Road, U-41RE Storrs, CT 06269-2041 (860) 486-3227 FAX: (860) 486-0349 cf@sba.uconn.edu This manuscript appeared as, Pace, R. Kelley, Ronald Barry, and C.F. Sirmans, "Spatial Statistics and Real Estate," Journal of Real Estate Finance and Economics, Volume 17, Number 1, 1998, p. 5-13. (contact data has been updated since publication and a misspelling corrected) Kluwer Academic Publishers owns the copyright to ... http://www.bus.lsu.edu/... ts/web_sintro/html/web_sintro2.htm |
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| 5: | Untitled Symposium on Spatial Data Handling (SDH) Article Citations 1992 (Listed in order of appearance in the proceedings) Volume 1 Rhind, David. The Information Infrastructure of GIS. Proceedings of the 5th International Symposium on Spatial Data Handling. Ed. P. Bresnahan, E. Corwin and D. Cowen. Charleston: IGU Commission of GIS, 1992. 1: 1-19. Edwards, Geoffrey. Error Minimization in Integrated GIS/IAS System Design. Proceedings of the 5th International Symposium on Spatial Data Handling. Ed. P. Bresnahan, E. Corwin and D. Cowen. Charleston: IGU Commission of GIS, 1992. 1: 20-29. Lupien, Tony, J. A. Hilbert, and S. H. Paschak. User Interface Lifecycle of Industrial GIS Applications. Proceedings of the 5th International Symposium on Spatial Data Handling. Ed. P. Bresnahan, E. Corwin and D. Cowen. Charleston: IGU Commission of GIS, 1992. 1: 30-39. Vijlbrief, Tom, and P. van Oosterom. The GEO+ System: an Extensible GIS. Proceedings of the 5th International Symposium on Spatial ... http://spatialodyssey.ursus.maine.edu/... eedings/ssdh92.html |
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| 6: | Spatial autocorrelation in vector-topological geographical information systems EGIS (1994), copyright EGIS Foundation. SPATIAL AUTOCORRELATION IN VECTOR-TOPOLOGICAL GEOGRAPHICAL INFORMATION SYSTEMS Henning Sten Hansen Kommunedata I/S Lautruppenparken 40, DK-2750 Ballerup, Denmark ABSTRACT The analysis of spatial patterns and the processes that produce and alter them is a central theme in geographic research, but spatial analysis has got increasing importance in many other disciplines. Spatial autocorrelation is a property that mapped data possesses whenever it exhibits an organized pattern, and analyses of spatial autocorrelation can be thought of as formal statistical investigations of the patterns on maps. This paper describes how to implement a measure of spatial autocorrelation into a standard vector-topological GIS - in this case ARC/INFO. The computation of autocorrelation coefficients is demonstrated using examples from human geography and economics. INTRODUCTION A modern "state of the art" GIS contains a lot data manipulation tools, such ... http://spatialodyssey.ursus.maine.edu/... b/egis/eg94140.html |
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| 7: | GIS/EM4 - Spatial uncertainty analysis of ecological models 4th International Conference on Integrating GIS and Environmental Modeling (GIS/EM4): Problems, Prospects and Research Needs. Banff, Alberta, Canada, September 2 - 8, 2000. Spatial uncertainty analysis of ecological models GIS/EM4 Henriette I. Jager Tom L. Ashwood Barbara L. Jackson Anthony W. King Abstract We evaluated the sensitivity of a habitat model and a source-sink population model to spatial uncertainty in landscapes with different statistical properties and for hypothetical species with different habitat requirements. Sequential indicator simulation generated alternative landscapes from a source map. Our results showed that spatial uncertainty was highest for landscapes in which suitable habitat was rare and spatially uncorrelated. Although, we were able to exert some control over the degree of spatial uncertainty by varying the sampling density drawn from the source map, intrinsic spatial properties (i.e., average frequency and degree of spatial autocorrelation) ... http://www.esd.ornl.gov/~zij/mypubs/GISEM4/index.htm |
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| 8: | Spatial Statistical Sites Spatial Statistical Sites A wide array of sites contain interesting spatial statistical content. Obviously, spatial statistics is a subset of statistics with many applications. Application areas include agriculture (yields between two adjacent plots are more similar than those far away), astronomy (gravity introduces dependence), biology (plants may repel or cluster), economics (wages vary regionally), geography (the study of such dependences), geology (minerals tend to cluster), manufacturing (defects tend to cluster), and real estate (houses in the same neighborhood share similarities). The increasing availability of georeferenced data coupled with the importance of space have led to an increased interest in spatial statistics. All applications areas have their canonical tools for modeling space. Interestingly, some of these fields have developed similar techniques. For example, Best Linear Unbiased Prediction (BLUP) was developed in geology and in economics independently. ... http://www.statistical.org/ |
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| 9: | Exploratory Spatial Data Analysis Table of Contents Top of Unit Advanced Organizer - Topics and Outcomes - Notes - Contents - Metadata Main Body 1. Introduction 2. Data Model 3. Classification 4. Non-Spatial 5. Spatial 6. Model Assessment 7. GIS and ESDA 8. Conclusions 9. References 10 Questions Evaluation Citation To the Curriculum NCGIA Core Curriculum in Geographic Information Science URL: "http:/www.ncgia.ucsb.edu/giscc/units/u128/u128_f.html" Exploratory Spatial Data Analysis Written by : Robert Haining and Stephen Wise The software used for the illustrations was written by Jingsheng Ma. Department of Geography and Sheffield Centre for Geographic Information and Spatial Analysis The University of Sheffield, S10 2TN, England. This unit was edited by C. Peter Keller, Department of Geography, University of Victoria, Canada. This unit is part of the NCGIA Core Curriculum in Geographic Information Science. These materials may be used for study, research, and education, but please credit the authors Robert ... http://www.ncgia.ucsb.edu/... la/giscc/units/u128/u128_f.html |
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| 10: | Posture Dependent Spatial Correlation: Similarity of Multiple CT-Derived Published in: Medical Imaging 1994: Physiology and Function from Multidimensional Images, Eric A. Hoffman, Raj S. Acharya, Editors, Proc. SPIE 2168, 380-392 (1994). Posture Dependent Spatial Correlation: Similarity of Multiple CT-Derived Pulmonary Structural and Functional Parameters Jehangir K. Tajik, Collin L. Olson, Gopal Sundaramoorthy and Eric A. Hoffman Department of Radiology University of Iowa College of Medicine Iowa City, IA 52242 [ home | search | contact us ] Table of Contents ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION CONCLUSION ACKNOWLEDGEMENTS REFERENCES ABSTRACT To help characterize the determinants of the spatial distribution of regional pulmonary structure and function and to characterize a spatial autocorrelation (SAC) approach, we have applied SAC statistics to our pulmonary cine x-ray CT data of regional pulmonary blood flow and to various computer derived models (cubes and pyramids, 3-D wedges, and lung shapes in which pure "flow" gradients ... http://everest.radiology.uiowa.edu/spie/paper2/paper2.html |
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