Geographic Information Analysis: Second Edition

Geographic Information Analysis: Second Edition

Volumn , Issue , 2010, Pages

  O'Sullivan, David ^a   Unwin, David J ^b  

^a UNIVERSITY OF AUCKLAND   (New Zealand)

^b UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84891576343     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9780470549094     Document Type: Book

References (426)

1. Baddeley, A. and Turner, R. (2005) Spatstat: an R package for analyzing spatial point patterns. Journal of Statistical Software, 12: 1-42.
2. Bivand, R. S., Pebesma, E. J., and Gomez-Rubio, V. (2008) Applied Spatial Data Analysis with R (New York: Springer).
3. Ihaka, R. and Gentleman, R. (1996). R: a language for data analysis and graphics. Journal of Computational and Graphical Statistics, 5: 299-314.
4. O'Sullivan, D. and Unwin, D. J. (2003) Geographic Information Analysis (Hoboken, NJ: Wiley).
5. Unwin, D. J. (1981) Introductory Spatial Analysis (London: Methuen).
6. Unwin, D. J. (2005) Fiddling on a different planet. Geoforum, 36: 681-684.
7. Bailey, T. C. and Gatrell, A. C. (1995) Interactive Spatial Data Analysis (Harlow, England: Longman).
8. Batty, M. and Longley, P. A. (1994) Fractal Cities: A Geometry of Form and Function (London: Academic Press).
9. Burrough, P. A. (1981) Fractal dimensions of landscapes and other environmental data, Nature, 294: 240-242.
10. Chrisman, N. R. (1998) Rethinking levels of measurement of cartography. Cartography and GIS, 25: 231-242.
11. Chrisman, N. R. (1999) A transformational approach to GIS operations. International Journal of Geographical Information Science, 13: 617-637.
12. Cressie, N. (1991) Statistics for Spatial Data (Chichester, England: Wiley).
13. DCDSTF-Digital Cartographic Data Standards Task Force (1988) The proposed standard for digital cartographic data. The American Cartographer, 15: 9-140.
14. Diggle, P. (1983) Statistical Analysis of Spatial Point Patterns (London: Academic Press).
15. Duckham, D. and Drummond, J. (2000) Assessment of error in digital vector data using fractal geometry, International Journal of Geographical Information Science, 14: 67-84.
16. Fisher, P. F. and Unwin, D. J., eds. (2005) Re-presenting GIS (Chichester, England: Wiley).
17. Ford, A. (1999) Modeling the Environment: An Introduction to System Dynamics Models of Environmental Systems (Washington, DC: Island Press).
18. Fotheringham, S., Brunsdon, C., and Charlton, M. (1999) Quantitative Geography: Perspectives on Spatial Data Analysis (London: Sage).
19. Goodchild, M. F. (1980) Fractals and the accuracy of geographical measures, Mathematical Geology, 12: 85-98.
20. Goodchild, M. F. and Mark, D. M. (1987) The fractal nature of geographic phenomena. Annals of the Association of American Geographers, 77: 265-278.
21. Haynes, R. M. (1975) Dimensional analysis: some applications in human geography. Geographical Analysis, 7: 51-67.
22. Haynes, R. M. (1978) A note on dimensions and relationships in human geography, Geographical Analysis, 10: 288-292.
23. Heuvelink, G. B. M. (1993) Error propagation in quantitative spatial modelling: applications in geographical information systems. Netherlands Geographical Studies. Utrecht: University of Utrecht.
24. Heuvelink, G. B. M. and Burrough, P. A. (1993) Error propagation in logical cartographic modelling using Boolean logic and continuous classification. International Journal of Geographical Information Systems, 7: 231-246.
25. Heuvelink, G. B. M., Burrough, P. A., and Stein, A. (1989) Propagation of errors in spatial modelling with GIS. International Journal of Geographical Information Systems, 3: 303-322.
26. Hearnshaw, H. and Unwin, D. J., eds. (1994) Visualisation in Geographical Information Systems, (London: Wiley).
27. Lam, N. and De Cola, L., eds. (1993) Fractals in Geography (Englewood Cliffs, NJ: Prentice Hall).
28. Langran, G. (1992) Time in Geographic Information Systems (London: Taylor & Francis).
29. Mandelbrot, B. M. (1977) Fractals: Form, Chance and Dimension (San Francisco: Freeman).
30. McHarg, I. (1969) Design with Nature (Philadelphia: Natural History Press).
31. Mitchell, A. (1999) The ESRI Guide to GIS Analysis (Redlands, CA: ESRI Press).
32. O'Sullivan, D. (2005) Geographical information science: time changes everything. Progress in Human Geography, 29(6): 749-756.
33. Raper, J. F. (2000) Multidimensional Geographic Information Science (London: CRC Press).
34. Richardson, L. F. (1961) The problem of contiguity. General Systems Yearbook, 6: 139-187.
35. Ripley, B. D. (1981) Spatial Statistics (Chichester, England: Wiley).
36. Ripley, B. D. (1988) Statistical Inference for Spatial Processes (Cambridge: Cambridge University Press).
37. Stevens, S. S. (1946) On the theory of scales of measurements. Science, 103: 677- 680.
38. Thurstain-Goodwin, M. and Unwin, D. J. (2000) Defining and delineating the central areas of towns for statistical monitoring using continuous surface representations, Transactions in GIS, 4(4): 305-317.
39. Tomlin, C. D. (1990) Geographic Information Systems and Cartographic Modelling (Englewood Cliffs, NJ: Prentice Hall).
40. Turcotte, D. L. (1997) Fractals and Chaos in Geology and Geophysics, 2nd ed. (Cambridge: Cambridge University Press).
41. Unwin, D. J. (1982) Introductory Spatial Analysis (London: Methuen).
42. Unwin, D. J. (1994) Visualization, GIS and cartography, Progress in Human Geography, 18: 516-522.
43. Unwin, D. J. (1995) Geographical information systems and the problem of error and uncertainty. Progress in Human Geography, 19: 549-558.
44. Velleman, P. F. and Wilkinson, L. (1993) Nominal, ordinal, interval, and ratio typologies are misleading. The American Statistician, 47: 65-72.
45. Wesseling, C. G., Karssenberg, D., Van Deursen, W. P. A., and Burrough, P. A. (1996) Integrating dynamic environmental models in GIS: the development of a Dynamic Modelling language. Transactions in GIS, 1: 40-48.
46. Wilson, A. G. (2000) Complex Spatial Systems (London: Pearson Education).
47. Worboys, M. F. (1992) A generic model for planar spatial objects. International Journal of Geographical Information Systems, 6: 353-372.
48. Worboys, M. F. (1995) Geographic Information Systems: A Computing Perspective (London: Taylor & Francis).
49. Worboys, M. F., Hearnshaw, H. M., and Maguire, D. J. (1990) Object-oriented data modeling for spatial databases. International Journal of Geographical Information Systems, 4: 369-383.
50. Zeiler, M. (1999) Modeling Our World: The ESRI Guide to Geodatabase Design (Redlands, CA: ESRI Press).
51. Doll, R. (1955) Etiology of lung cancer. Advances in Cancer Research, 3: 1-50.
52. Freedman, D., Pisani, R., and Purves, R. (1998) Statistics, 3rd ed. (New York: W. W. Norton).
53. Gatrell, A. C. (1983) Distance and Space: A Geographical Perspective (Oxford: Oxford University Press).
54. Gehlke, C. E. and Biehl, K. (1934) Certain effects of grouping upon the size of the correlation coefficient in census tract material. Journal of the American Statistical Association, 29(185): 169-170.
55. Okabe, A., Boots, B., Sugihara, K., and Chiu, S. N. (2000) Spatial Tessellations: Concepts and Applications of Voronoi Diagrams, 2nd ed. (Chichester, England: Wiley).
56. Okabe, A., Boots, B., and Sugihara, K. (1994) Nearest neighborhood operations with generalized Voronoi diagrams: a review. International Journal of Geographical Information Systems, 8: 43-71.
57. Okabe, A., Satoh, T., Furuta, T., Suzuki, A., and Okano, K. (2008) Generalized network Voronoi diagrams: concepts, computational methods, and applications. International Journal of Geographical Information Science, 22: 965- 994.
58. Openshaw, S. (1983) The Modifiable Areal Unit Problem. Concepts and Techniques in Modern Geography 38, 41 pages (Norwich, England: Geo Books). Available at http://www.qmrg.org.uk/catmog.
59. Openshaw, S., and Taylor, P. J. (1979) A million or so correlation coefficients: three experiments on the modifiable areal unit problem in Wrigley, N. (ed.), Statistical Methods in the Spatial Sciences (London: Pion), pp. 127-144.
60. Tobler, W. R. (1970) A computer movie simulating urban growth in the Detroit region. Economic Geography, 46: 234-240.
61. Anselin, L. (1996) The Moran scatterplot as an ESDA tool to assess local instability in spatial association. In: M. Fischer, H. J. Scholten, and D. Unwin, eds., Spatial Analytical Perspectives on GIS, (London: Taylor & Francis): pp. 111-125.
62. Bertin, J. (1983) Semiology of Graphics (Madison: University of Wisconsin Press).
63. Brody, H., RussellPip, M., Vinten-Johnasen, P., Paneth, N., and Rachman, S. (2000) Map-making and myth-making in Broad Street: the London cholera epidemic, 1854. The Lancet, 356(9223): 64-68.
64. Brunsdon, C. (1995) Estimating probability surfaces for geographical point data: an adaptive technique. Computers and Geosciences, 21: 877-894.
65. Choynowski, M. (1959) Maps based on probabilities. Journal of the American Statistical Association, 54: 385-388.
66. Cressie, N. A. (1993) Statistics for Spatial Data, rev. ed. (Hoboken, NJ: Wiley), pp. 385-393.
67. CRU, Census Research Unit. (1980) People in Britain-A Census Atlas (London: Her Majesty's Stationery Office).
68. Dent, B. D. (1990) Cartography: Thematic Map Design (DuBuque, IA: WCB Publishers).
69. DiBiase, D., MacEachren, A. M., Krygier, J., and Reeves, C. (1992) Animation and the role of map design in scientific visualization. Cartography and Geographic Information Systems, 19: 201-214.
70. Dobson, M. W. (1973) Choropleth maps without class intervals? A comment. Geographical Analysis, 5: 358-360.
71. Dodge, M., McDerby, M., and Turner, M., eds. (2008) Geographic Visualization (Chichester, England: Wiley).
72. Dodge, M., and Perkins, C. (2008) Reclaiming the map: British geography and ambivalent cartographic practice. Environment and Planning A, 40: 1271-1276.
73. Dolan, M. E., Holden, C. C., Beard, M. K., and Bult, C. J. (2006) Genomes as geography: using GIS technology to build interactive genome feature maps. BMC Bioinformatics, 7: 416 (available at www.biomedcentral.com/1471-2105/7/416).
74. Donnay, J. P. and Unwin, D. J. (2001) Modelling geographical distributions in urban areas. In: J. P. Donnay, M. J. Barnsley, and P. A. Longley, eds., Remote Sensing and Urban Analysis, GISDATA 9 (London: Taylor & Francis), pp. 205-224.
75. Dorling, D. F. L. (1992) Visualizing people in time and space. Environment and Planning B: Planning and Design, 19: 613-637.
76. Dorling, D. (1994) Cartograms for visualizing human geography. In: H. Hearnshaw, and D. Unwin, eds., Visualization in Geographical Information Systems (Chichester, England: Wiley), pp. 85-102.
77. Dorling, D. F. L. (1995) A New Social Atlas of Britain (Chichester, England: Wiley).
78. Dorling, D. (1996) Area cartograms: their use and creation. Concepts and Techniques in Modern Geography, 59, 69 pages (Norwich, England: Geo Books). Available at http://www.qmrg.org.uk/catmog.
79. Dorling, D., Newman, M., and Barford, A. (2008) The Atlas of the Real World (London: Thames and Hudson) (also available at http://www.worldmapper.org).
80. Dykes, J. A., Fisher, P. F., Stynes, K., Unwin, D., and Wood, J. (1997) The use of the landscape metaphor in understanding population data. Environment and Planning, B: Planning and Design, 26: 281-295.
81. Dykes, J. A., MacEachren, A. M., and Kraak, M.-J., eds., (2005) Exploring Geovisualization (Amsterdam: Elsevier).
82. Dykes, J. and Unwin, D. J. (2001) Maps of the Census: A Rough Guide (available at http://www.agocg.ac.uk/reports/visual/casestud/dykes/dykes.pdf).
83. Earnshaw, R. A. and Wiseman, N. (1992) An Introduction to Scientific Visualization (Berlin: Springer-Verlag).
84. Evans, I. S. (1977) The selection of class intervals. Transactions of the Institute of British Geographers, Vol. 2, 98-124.
85. Fabrikant, S. I. (2003) Commentary on ''A History of Twentieth-Century American Academic Cartography'' by Robert McMaster and Susanna McMaster. Cartography and Geographic Information Science, 30: 81-84.
86. Fabrikant, S. I., Montello, D. R., Ruocco, M., and Middleton, R. S. (2004) The distance-similarity metaphor in network-display spatializations. Cartography and Geographic Information Science, 31: 237-252.
87. Ferreira, J., Jr. and Wiggins, L. L. (1990) The density dial: a visualization tool for thematic mapping. Geo Info Systems, 10: 69-71.
88. Fisher, P. F., Dykes, J., and Wood, J. (1993) Map design and visualisation. The Cartographic Journal, 30: 36-42.
89. Fisher, P. F. and Unwin, D. J., eds. (2002) Virtual Reality in Geography (London: Taylor & Francis).
90. Fisher, P., Wood, J., and Cheng, T. (2004) Where is Helvellyn? Fuzziness of multiscale landscape morphometry. Transactions of the Institute of British Geographers, 29: 106-128.
91. Foxell, S. (2008) Mapping England (London: Black Dog Publishing).
92. Gastner, M. T. and Newman, M. E. J. (2004) Diffusion-based method for produing density equalizing maps. Proceedings of the National Academy of Science, USA, 101: 7499-7504.
93. Gatrell, A. C. (1983) Distance and Space: A Geographical Perspective (Oxford: Clarendon Press).
94. Gatrell, A. C, and Gould, P. (1979) A micro-geography of team games: graphical explorations of structural relations. Area 11: 275-278.
95. Gusein-Zade, S. M. and Tikunov, V. (1993) A new technique for constructing continuous cartograms. Cartography and Geographic Information Systems, 20: 167-173.
96. Hall, S. S. (1992) Mapping the Next Millennium: The Discovery of New Geographies (New York: Random House).
97. Hearnshaw, H. and Unwin, D. J., eds. (1994) Visualisation and GIS (London: Wiley).
98. Hudson-Smith, A. (2008) Digital Geography: Geographic Visualisation for Urban Environments (London: UCL/CASA).
99. Hunter, J. M. and Young, J. C. (1968) A technique for the construction of quantitative cartograms by physical accretion models. Professional Geographer, 20: 402-407.
100. Johnson, S. (2006) The Ghost Map (New York: Riverhead; London: Penguin Books).
101. Keim, D., North, S., and Panse, C. (2004) CartoDraw: a fast algorithm for generating contiguous cartograms. IEEE Transactions on Visualization and Computer Graphics, 10: 95-110.
102. Kennelly, P. J. and Kimerling, A. J. (2001) Hillshading alternatives: new tools produce classic cartographic effects. ArcUser (available at http://www.esri. com/news/arcuser/0701/althillshade.html.
103. Koch, T. (2004) The map as intent: variations on the theme of John Snow Cartographica, 39: 1-13.
104. Koch, T. (2005) Cartographies of Disease: Maps, Mapping and Medicine (Redlands, CA: ESRI Press).
105. Koch, T. and Denke, K. (2004) Medical mapping: the revolution in teaching- and using-maps for the analysis of medical issues. Journal of Geography, 103: 76-85.
106. Kraak, M.-J. (2006) Why maps matter in GIScience. The Cartographic Journal, 43: 82-89.
107. Krygier, J. and Wood, D. (2005) Making Maps: A Visual Guide to Map Design for GIS (New York: Guildford Press).
108. Langford, I. (1994) Using empirical Bayes estimates in the geographical analysis of disease risk. Area, 26: 142-190.
109. Langford, M. and Unwin, D. J. (1994) Generating and mapping population density surfaces within a geographical information system. The Cartographic Journal, 31: 21-26.
110. MacEachren, A. M. and Fraser Taylor, D. R., eds. (1994) Visualisation in Modern Cartography (Oxford: Pergamon Press).
111. Mackay, J. R. (1949) Dotting the dot map. Surveying and Mapping, 9: 3-10.
112. Marshall, R. J. (1991) Mapping disease and mortality rates using empirical Bayes estimators. Applied Statistics, 40: 283-294.
113. Martin, D. (1989) Mapping population data from zone centroid locations. Transactions of the Institute of British Geographers, 14: 90-97.
114. Mennis, J. (2003) Generating surface models of population using dasymetric mapping. Professional Geographer, 55(1): 31-42.
115. Mennis, J. (2006) Mapping the results of geographically weighted regression. Cartographic Journal, 43(2): 171-179.
116. Monmonier, M. (1989) Geographic brushing: enhancing exploratory analysis of the scatterplot matrix. Geographical Analysis, 21: 81-84.
117. Monmonier, M. (1991) How to Lie with Maps (Chicago: University of Chicago Press).
118. Robinson, A. H., Morrison, J. L., Muehrcke, P. C., Kimerling, A. J., and Guptill, S. C. (1995) Elements of Cartography, 6th ed. (London: Wiley).
119. Schwartz, S. (2008) The Mismapping of America (Rochester, NY: University of Rochester Press).
120. Skoda, L. and Robertson, J. C. (1972) Isodemographic Map of Canada (Ottawa: Lands Directorate, Department of Environment, Geographical Papers, 50). See also http://www.csiss.org/classics/content/27.
121. Skupin, A. and Fabrikant, S. I. (2003) Spatialization methods: a cartographic research agenda for non-geographic information visualization. Cartography and Geographic Information Science, 30: 95-119.
122. Thurstain-Goodwin, M. and Unwin, D. J. (2000) Defining and delimiting the central areas of towns for statistical monitoring using continuous surface representations. Transactions in GIS, 4: 305-317.
123. Tobler, W. R. (1963) Geographic area and map projections. Geographical Review, 53: 59-78.
124. Tobler, W. R. (1970) A computer movie simulating urban growth in the Detroit region. Economic Geography, 46: 234-240.
125. Tobler, W. R. (1973) Choropleth maps without class intervals. Geographical Analysis, 5: 26-28.
126. Tobler, W. (2004) Thirty-five years of computer cartograms. Annals of the Association of American Geographers, 94: 1-58.
127. Unwin, D. J. (1994) Visualization, GIS and cartography. Progress in Human Geography, 18: 516-522.
128. Winchester, S. (2002) The Map That Changed the World (London: Penguin Books).
129. Wood, J. D., Fisher, P. F., Dykes, J. A., Unwin, D. J., and Stynes, K. (1999) The use of the landscape metaphor in understanding population data. Environment and Planning B: Planning and Design, 26: 281-295.
130. Wright, J. K. (1936) A method of mapping densities of population with Cape Cod as an example. Geographical Review, 26: 103-110.
131. Barabàsi, A.-L. (2002) Linked: The New Science of Networks (Cambridge, MA: Perseus).
132. Bastin, G., Lorent, B., Duque, C., and Gevers, M. (1984) Optimal estimation of the average rainfall and optimal selection of rain gauge locations. Water Resources Research, 20: 463-470.
133. Berg, H. C. (1993) Random Walks in Biology (Princeton, NJ: Princeton University Press).
134. Cressie, N. A. C. (1991) Statistics for Spatial Data (Chichester, England: Wiley).
135. Getis, A. and Boots, B. (1978) Models of Spatial Processes (Cambridge: Cambridge University Press).
136. Gleick, J. (1987) Chaos: Making a New Science (New York: Viking Penguin).
137. Horowitz, M. (1965) Probability of random paths across elementary geometrical Shapes. Journal of Applied Probability, 2(1): 169-177.
138. Isaaks, E. H. and Srivastava, R. M. (1989) An Introduction to Applied Geostatistics (New York: Oxford University Press).
139. Jones, J. A. A. (1978) The spacing of streams in a random walk model. Area, 10: 190-197.
140. King, L. J. (1984) Central Place Theory (Beverly Hills, CA: Sage).
141. Ling, R. F. (1973) The expected number of components in random linear graphs. Annals of Probability, 1: 876-881.
142. Mardia, K. V. (1972) Statistics of Directional Data (London: Academic Press).
143. Mardia, K. V. and Jupp, P. E. (1999) Directional Statistics (Chichester, England: Wiley).
144. Milton, L. E. (1966) The geomorphic irrelevance of some drainage net laws. Australian Geographical Studies, 4: 89-95.
145. Shreve, R. L. (1966) Statistical law of stream numbers. Journal of Geology, 74: 17-37.
146. Taylor, P.J. (1971) Distances within shapes: an introduction to a family of finite frequency distributions. Geografiska Annaler, B53: 40-54.
147. Tinkler, K. J. (1977) An Introduction to Graph Theoretical Methods in Geography. Concepts and Techniques in Modern Geography; 14,56 pages (Norwich, England: Geo Books). Available at http://www.qmrg.org.uk/catmog.
148. Tobler, W. (1970) A computer movie simulating urban growth in the Detroit region. Economic Geography, 46: 23-40.
149. Watts, D. J. (2003) Six Degrees: The Science of a Connected Age (New York: Norton).
150. Werritty, A. (1972) The topology of stream networks. In: R.J. Chorley, ed., Spatial Analysis in Geomorphology (London: Methuen), pp. 167-196.
151. Baddeley, A. and Turner, R. (2005). Spatstat: an R package for analyzing spatial point patterns. Journal of Statistical Software, 12 (6): 1-42.
152. Bailey, T. C., and Gatrell, A. C. (1995) Interactive Spatial Data Analysis (Harlow, England: Addison Wesley Longman).
153. Clark, P. J. and Evans, F. C. (1954) Distance to nearest neighbour as a measure of spatial relationships in populations. Ecology, 35: 445-453.
154. Crozier, M. J. (1976) On the origin of the Peterborough drumlin field: testing the dilatancy theory. Canadian Geographer 19: 181-195.
155. Davis, J. H., Howe, R. W., and Davis, G. J. (2000) A multi-scale spatial analysis method for point data. Landscape Ecology, 15: 99-114.
156. Diggle, P. (2003) Statistical Analysis of Spatial Point Patterns (London: Arnold).
157. Gatrell, A. C., Bailey, T. C., Diggle, P. J., and Rowlingson, B. S. (1996) Spatial point pattern analysis and its application in geographical epidemiology. Transactions of the Institute of British Geographers, NS 21: 256-274.
158. Greig-Smith, P. (1964), Quantitative Plant Ecology (London: Butterworths).
159. Gr€unbaum, B. and Shephard, G. C. (1987) Tilings and Patterns (New York: W. H. Freeman).
160. Levine, N.and Associates (2007) CrimeStat III: A Spatial Statistics Program for the Analysis of Crime Locations (available at http://www.icpsr.umich.edu/CRIMESTAT/).
161. Numata, M. (1961) Forest vegetation in the vicinity of Choshi. Coastal flora and vegetation at Choshi, Chiba Prefecture. IV. Bulletin of Choshi Marine Laboratory, Chiba University 3, 28-48 (in Japanese).
162. Perry, G. L. W., Miller, B. P., and Enright, N. J. (2006) A comparison of methods for the statistical analysis of spatial point patterns in plant ecology. Plant Ecology, 187: 59-82.
163. Ripley, B. D. (1976) The second-order analysis of stationary point processes. Journal of Applied Probability, 13: 255-266.
164. Ripley, B. D. (1977) Modelling spatial patterns. Journal of the Royal Statistical Society, Series B, 39: 172-212.
165. Ripley, B. D. (1988) Statistical Inference for Spatial Processes (Cambridge: Cambridge University Press).
166. Rogers, A. (1974) Statistical Analysis of Spatial Dispersion (London: Pion).
167. Rose, J. and Letzer, J. M. (1976) Drumlin measurements: a test of the reliability of data derived from 1:25,000 scale topographic maps. Geological Magazine, 112: 361-371.
168. Smalley, I. J.andUnwin,D.J.(1968)Theformationandshapeofdrumlinsandtheir distribution and orientation in drumlin fields. Journal of Glaciology, 7: 377-390.
169. Strauss, D. J. (1975) A model for clustering. Biometrika, 63: 467-475.
170. Thomas, R. W. (1977) An introduction to quadrat analysis. Concepts and Techniques in Modern Geography, 12, 41 pages (Norwich, England: Geo Books). Available at http://www.qmrg.org.uk/catmog.
171. Thompson, H. R. (1956) Distribution of distance to nth neighbour in a population of randomly distributed individuals. Ecology, 37: 391-394.
172. Trenhaile, A. S. (1971) Drumlins, their distribution and morphology. Canadian Ceographer, 15: 113-26.
173. Trenhaile, A. S. (1975) The morphology of a drumlin field. Annals of the Association of American Geographers, 65: 297-312.
174. Wiegand, T. and Moloney, K. A., (2004) Rings, circles and null models for point patterns analysis in ecology. Oikos, 1104: 209-229.
175. Yamada, I. and Rogerson, P. A. (2003) An empirical comparison of edge effect correction methods applied to K-function analysis. Geographical Analysis, 37: 95-109.
176. Ahuja, N. (1982) Dot pattern processing using Voronoi neighbourhoods. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI 3: 336343.
177. Baddeley, A. J., Moller, J., and Waagespetersen, R. (2000) Non- and semi-parametric estimation of interaction in inhomogengeous point patterns. Statistica Neerlandica, 54: 329-350.
178. Baddeley, A. and Turner, R. (2005) Spatstat: an R package for analyzing spatial point patterns. Journal of Statistical Software, 12:1-42. (For a comprehensive set of resources related to this package, see http://school.maths.uwa.edu.au/homepages/adrian/.)
179. Bailey, T. C. and Gatrell, A. C. (1995) Interactive Spatial Data Analysis (Harlow, Essex, England: Longman).
180. Besag, J. and Newell, J. (1991) The detection of clusters in rare diseases. Journal ofthe Royal Statistical Society, Series A, 154: 143-155.
181. Bithell, J. F. (1990) An application of density estimation to geographical epidemiology. Statistics in Medicine, 9: 691-701.
182. Bithell, J.F.,Keegan, T.J.,Kroll,H.E.,Murphy,M.F. G.,andVincent, T.J. (2008) Childhood leukemia near British nuclear installations: methodological issues and recent results. Radiation Protection Dosimetry, 132: 191-197.
183. Bithell, J. C. and Stone, R. A. (1989) On statistical methods for analyzing the distribution of cancer cases near nuclear installations. Journal of Epidemiology and Community Health, 43: 79-85.
184. Bivand, R. S., Pebesma, E. J., and Gomez-Rubio, V. (2008) Applied Spatial Data Analysis with R (New York: Springer).
185. Black, Sir D. (1984) Investigation of the Possible Increased Incidence of Cancer in West Cumbria (London: Her Majesty's Stationery Office).
186. Bolstad, W. M. (2007) Introduction to Bayesian Statistics, 2nd ed. (Hoboken, NJ: Wiley).
187. Craft, A. W. and Birch, G. M. (1983) Childhood cancers in Cumbria. The Lancet, 322: 1299.
188. Craft, A. W. and Openshaw, S., and Gardner, M. J. (1985) Childhood cancers in West Cumbria. The Lancet, 325: 403-404.
189. Craft, A. W, Openshaw, S., and Birch, J. (1984) Apparent clusters of childhood lymphoid malignancy in Northern England. The Lancet, 324: 96-97.
190. Cuzick, J. and Edwards, R. (1990) Spatial clustering for inhomogeneous populations. Journal ofthe Royal Statistical Society, Series B, 52: 73-104.
191. Diggle, P. J. (1990) A point process modelling approach to raised incidence of a rare phenomenon in the vicinity of a prespecified point. Journal of the Royal Statistical Society, Series A, 153: 349-362.
192. Edwards, A. W. F. (1992) Likelihood, Expanded Edition (Baltimore, MD: Johns Hopkins University Press).
193. Gardner, M. J. (1985) Childhood cancer in West Cumbria. The Lancet, 325: 403404.
194. Gardner, M. J. (1989) Review of reported increases of childhood cancer rates in the vicinity of nuclear installations. Journal ofthe Royal Statistical Society, Series A, 152: 307-325.
195. Gardner, M. J., Snee, M. P., Hall, A. J., Downes, S., Powell, C. A., and Terrell, J. D. T. (1990) Results ofcase-control study ofleukemia and lymphoma in young persons resident in West Cumbria. British Medical Journal, 300(6722): 423-429.
196. Gardner, M. J., and Winter, P. D. (1984) Mortality in Cumberland during 195978 with reference to cancer in young people around Windscale. The Lancet, 323: 216-218.
197. Gatrell, A. C., Bailey, T. C., Diggle, P. J., and Rowlingson, B. S. (1996) Spatial point pattern analysis and its application in geographical epidemiology, Transactions ofthe Institute ofBritish Geographers, NS 21: 256-274.
198. Gould, P. R. (1970) Is statistix inferens, the geographical name for a wildgoose? Economic Geography, 46: 439-448.
199. Harvey, D. W. (1966) Geographical processes and the analysis of point patterns. Transactions ofthe Institute ofBritish Geographers, 40: 85-95.
200. Harvey, D. W. (1968) Some methodological problems in the use ofNeyman type A and negative binomial distributions for the anaysis of point patterns. Transactions ofthe Institute ofBritish Geographers, 44: 85-95.
201. Heasman, M. A., Kemp, I. W., Urquhart, J. D., and Black, R. (1986) Childhood leukaemia in Northern Scotland. The Lancet, 327: 266.
202. Hills, M. and Alexander, F. (1989) Statistical methods used in assessing the risk ofdisease near a source ofpossible environmental pollution: a review. Journal ofthe Royal Statistical Society, Series A, 152: 353-363.
203. Johnson, S. (2006) The Ghost Map (New York: Riverhead; London: Penguin Books).
204. Kinlen, L. (1988) Evidence for an infective cause of childhood leukemia-comparison of a Scottish New Town with nuclear reprocessing sites in Britain, The Lancet 332: 1323-1327.
205. Kulldorff, M. (1997) A spatial scan statistic. Communications in Statistics: Theory and Methods, 26: 1481-1496.
206. Kulldorff, M. (2006) Tests ofspatial randomness adjusted for an inhomogeneity: a general framework. Journal of the American Statistical Association, 101: 1289-1305.
207. Kulldorf, M. and Nagarwalla, N. (1995) Spatial disease clusters: detection and inference. Statistics in Medicine, 14: 799-810.
208. Levine, N. (2004) CrimeStat III: A Spatial Statistics Program for the Analysis of Crime Incident Locations (version 3.0) (Houston, TX: National Institute of Justice; Washington, DC: and Ned Levine & Associates. (see also http://www.nedlevine.com/nedlevine17.htm).
209. Lloyd, O. L., MacDonald, J., and Lloyd, M. M. (1984) Mortality from lymphatic and haematopoietic cancer in Scottish coastal towns. The Lancet, 324: 95-96.
210. Okabe, A., Boots, B., Sugihara, K., and Chiu, S. N. (2000) Spatial Tessellations: Concepts and Applications ofVoronoi Diagrams, 2nd ed. (Chichester, England: Wiley).
211. Openshaw, S., Charlton, M., Craft, A. W., and Birch, J. M. (1988) Investigation of leukaemia clusters by use ofa geographical analysis machine. The Lancet, 331 (8580): 272-273.
212. Openshaw, S., Charlton, M., Wymer, C., and Craft, A. (1987) Developing a mark 1 Geographical Analysis Machine for the automated analysis of point data sets, International Journal of Geographical Information Systems,1: 335-358.
213. Perry, G. L. W., Enright, N. J., Miller, B. P., and Lamont, B. B. (2008) Spatial patterns in species-rich sclerophyll shrublands of southwestern Australia. Journal ofVegetation Science, 19: 705-716.
214. Perry, G. L. W., Miller, B. P., and Enright, N. J. (2006) A comparison of methods for the statistical analysis of spatial point patterns in plant ecology. Plant Ecology, 187: 59-82.
215. Rushton, G. and Lolonis, P. (1996) Exploratory spatial analysis of birth defect rates in an urban population. Statistics in Medicine, 15: 717-726.
216. Schabenberger, O. and Gotway, C. A. (2005) Statistical Methods for Spatial Data Analysis (London: Chapman & Hall).
217. Urquhart, J. and Cutler, J. A. (1985) Incidence of childhood cancer in west Cumbria. The Lancet, 325: 172.
218. Urquhart, J., Palmer, M., and Cutler, J. (1984) Cancer in Cumbria: the Wind-scale connection. The Lancet, 323: 217-218.
219. Vincent, P. J., Howarth, J. M., Griffiths, J. C., and Collins, R. (1976) The detection of randomness in plant patterns. Journal of Biogeography,3: 373-380.
220. Worboys, M. F. (1995) Geographic Information Systems: A Computing Perspective (London: Taylor & Francis).
221. Anselin, L. (1995) Local indicators of spatial association-LISA. Geographical Analysis, 27: 93-115.
222. Bavaud, F. (1998) Models for spatial weights: a systematic look. Geographical Analysis, 30: 152-171.
223. Berry, J. K., Buckley, D. J., and McGarigal, K. (1998) Fragstats.arc: Integrating ARC/INFO with the Fragstats landscape analysis program. Proceedings of the 1998 ESRI User Conference, San Diego, CA.
224. Bivand, R. S., Pebesma, E. J., and Gomez-Rubio, V. (2008) Applied Spatial Data Analysis with R (New York: Springer).
225. Boots, B. N. (1977) Contact number properties in the study of cellular networks. Geographical Analysis, 9: 379-387.
226. Boots, B. N. (1983) Comments on using eigenfunctions to measure structural properties of geographic networks. Environment and Planning, Series A, 14: 1063-1072.
227. Boots, B. N. (1984) Evaluating principal eigenvalues as measures of network structures. Geographical Analysis, 16: 270-275.
228. Boots, B. and Tiefelsdorf, M. (2000) Global and local spatial correlation in bounded regular tessellations. Journal of Geographical Systems, 2: 319-348.
229. Boyce, R. and Clark, W. (1964) The concept of shape in geography. Geographical Review, 54: 561-572.
230. Cerny, J. W. (1975) Sensitivity analysis of the Boyce-Clark shape index. Canadian Geographer, 12: 21-27.
231. Clark, W. and Gaile, G. L. (1975) The analysis and recognition of shapes. Geografiska Annaler, 55B: 153-163.
232. Cliff, A.D. and Ord, J.K. (1973) Spatial Autocorrelation (London: Pion).
233. Coppock, J. T. (1955) The relationship of farm and parish boundaries: a study in the use of agricultural statistics. Geographical Studies, 2: 12-26.
234. Coppock, J. T. (1960) The parish as a geographical statistical unit. Tijdschrift voor Economische en Sociale Geographie, 51: 317-326.
235. DeZonia, B. and Mladenoff, D. J. (2004) IAN-raster image analysis software program. Department of Forest Ecology and Management, University of Wisconsin, Madison, WI. Available at http://landscape.forest.wisc.edu/projects/IAN/.
236. Frolov, Y. S. (1975) Measuring the shape of geographical phenomena: a history of the issue. Soviet Geography, 16: 676-687.
237. Frolov, Y. S. and Maling, D. H. (1969) The accuracy of area measurement by point counting techniques. Cartographic Journal, 6: 21-35.
238. Garreau, J. (1992) Edge City (New York: Anchor).
239. Getis, A. and Aldstat, J. (2004) Constructing the spatial weights matrix using a local statistic. Geographical Analysis, 36: 90-104.
240. Gierhart, J. W. (1954) Evaluation of methods of area measurement. Survey and Mapping, 14: 460-469.
241. Griffith, D. (1996) Spatial autocorrelation and eigenfunctions of the geographic weights matrix accompanying geo-referenced data. Canadian Geographer, 40: 351-367.
242. Houghton, R. A., Skole, D. L., Nobre, C. A., Hackler, J. L., Lawrence, K. T., and Chomentowski, W. H. (2000) Annual fluxes or carbon from deforestation and regrowth in the Brazilian Amazon. Nature, 403(6767): 301-304.
243. Lee, D. R. and Sallee, G. T. (1970) A method of measuring shape. Geographical Review, 60: 555-563.
244. McGarigal, K., Cushman, S. A., Neel, M. C., and Ene, E. (2002) FRAGSTATS: Spatial Pattern Analysis Program for Categorical Maps. Computer software program produced at the University of Massachusetts, Amherst. Available at www.umass.edu/landeco/research/fragstats/fragstats.html.
245. Medda, F., Nijkamp, P., and Rietveld, P. (1998) Recognition and classification of urban shapes. Geographical Analysis, 30(4): 304-14.
246. Moran, P. A. P. (1950) Notes on continuous stochastic phenomena. Biometrika, 37: 17-33.
247. Nepstad, D. C., Verissimo, A., Alencar, A., Nobre, C., Lima, E., Lefebvre, P., Schlesinger, P., Potter, C., Moutinho, P., Mendoza, E., Cochrane, M., and Brooks, V. (1999), Large-scale impoverishment of Amazonian forests by logging and fire. Nature, 398(6727): 505-508.
248. Smith, B. and Varzi, A. C. (2000) Fiat and bona fide boundaries. Philosophy and Phenomenological Research, 60(2): 401-420.
249. Tinkler, K. (1972). The physical interpretation of eigenfunctions of dichotomous matrices. Transactions of the Institute of British Geographers, 55: 17-46.
250. Tobler, W. R. (1970) A computer movie simulating urban growth in the Detroit region. Economic Geography, 46: 234-240.
251. Turner, M. G., Gardner, R. H., and O'Neill, R. V. (2001) Landscape Ecology in Theory and Practice: Pattern and Process (New York: Springer-Verlag).
252. Unwin, D. J. (1981) Introductory Spatial Analysis (London: Methuen).
253. Wentz, E. A. (2000) A shape definition for geographic applications based on edge, elongation and perforation. Geographical Analysis, 32: 95-112.
254. Wood, W. F. (1954) The dot planimeter: a new way to measure area. Professional Geographer, 6: 12-14.
255. Worboys, M. F. and Duckham, M. (2004) GIS: A Computing Perspective (London: Taylor & Francis).
256. Zhang, D. and Lu, G. (2004) Review of shape representation and description techniques. Pattern Recognition, 37(1): 1-19.
257. Anselin, L. (1988) Spatial Econometrics: Methods and Models (Dordrecht, Netherlands: Kluwer Academic).
258. Anselin, L. (1995) Local indicators of spatial association-LISA. Geographical Analysis, 27 (2): 2-93.
259. Anselin, L. and Florax, R. J. G. M., Eds. (1995) New Directions in Spatial Econometrics (Berlin and New York: Springer-Verlag).
260. Anselin, L., Florax, R. J. G. M., and Rey, S. J., Eds. (2004) Advances in Spatial Econometrics: Methodology, Tools and Applications (Berlin and New York: Springer-Verlag).
261. Bleasdale A. and Chan, Y. K. (1972) Orographic influences on the distribution of precipitation. In: Distribution of Precipitation in Mountainous Areas (Geneva: World Meteorological Office), pp. 322-333.
262. Brunsdon, C., Fotheringham, A. S., and Charlton, M. E. (1996) Geographically weighted regression: a method for exploring spatial nonstationarity. Geographical Analysis, 28 (4): 4-281.
263. Brunsdon, C., McClatchey, J., and Unwin, D. J. (2001) Spatial variations in the average rainfall/altitude relationship in Great Britain: an approach using geographically weighted regression. International Journal of Climatology, 21: 455-466.
264. Casetti, E. and Can, A. (1999) The econometric estimation and testing of DARP models. Journal of Geographical Systems, 1: 91-106.
265. Cleveland, W. S. (1979) Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association, 74: 829-836.
266. Cleveland, W. S. and Devlin, S. J. (1988) Locally weighted regression: an approach to regression analysis by local fitting. Journal of the American Statistical Association, 83: 596-610.
267. Fotheringham, A. S. (1997) Trends in quantitative methods I: stressing the local. Progress in Human Geography, 21 (1): 1-88.
268. Fotheringham, A. S., Charlton, M. E., and Brunsdon, C. (2002) Geographically Weighted Regression: The Analysis of Spatially Varying Relationships (Chichester, England: Wiley).
269. Getis, A. and Ord, J. K. (1992) The analysis of spatial association by use of distance statistics. Geographical Analysis, 24 (3): 3-189.
270. Jones, K. (1991) Multi-level models for geographical research. Concepts and Techniques in Modern Geography, 54, (48 pages Norwich, England: Environmental Publications). Available at http://www.gmrg.org.uk/catmog.
271. Ord, J. K. and Getis, A. (1995) Local spatial autocorrelation statistics: distributional issues and an application. Geographical Analysis, 27 (4): 4-286.
272. Sidak, Z. (1967) Rectangular confidence regions for the means of multivariate normal distributions. Journal of the American Statistical Association, 62: 626-633.
273. Tukey, J. W. (1977) Exploratory Data Analysis (Reading, MA: Addison-Wesley).
274. Unwin, D. J. (1996) GIS, spatial analysis and spatial statistics. Progress in Human Geography, 20 (4): 4-540.
275. Braile, L. W. (1978) Comparison of four random-to-grid methods. Computers and Geosciences, 14: 341-349.
276. Burrough, P. A. and McDonnell, R. (1998) Principles of Geographical Information Systems, 2nd ed. (Oxford: Clarendon Press).
277. Clarke, J. I. (1966) Morphometry from maps. In: G. H. Dury (ed.), Essays in Geomorphology (London: Heinemann), pp. 235-274.
278. Clarke, J. I. and Orrell, K. (1958) An assessment of some morphometric methods. Durham, England: University of Durham Occasional Paper No. 2.
279. Davis, J. C. (2003) Statistics and Data Analysis in Geology, 3rd ed. (Hoboken, NJ: Wiley).
280. Davis, J.C. (1976) Contouring algorithms. In: AUTOCARTO II, Proceedings of the International Symposium on Computer-Assisted Cartography (Washington, DC: U.S. Bureau of the Census), pp. 352-359.
281. De Floriani, L. and Magillo, P. (1994) Visibility algorithms on triangulated terrain models. International Journal of Geographical Information Systems, 8 (1): 13-41.
282. DeMers, M. (2001) GIS Modeling in Raster (New York: Wiley).
283. Dury, G. H. (1972) Map Interpretation, 4th ed. (London: Pitman), pp. 167-177.
284. Evans, I. S. (1972) General geomorphometry, derivatives of altitude and descriptive statistics. In: R. J. Chorley, ed., Spatial Analysis in Geomorphology (London, England: Methuen), pp. 19-90.
285. Hardy, R. L. (1971) Multiquadric equations of topography and other irregular surfaces. Journal of Geophysical Research, 76 (8): 1905-1915.
286. Li, X. and Hodgson, M. E. (2004) Vector field data model and operations. GIScience and Remote Sensing, 41 (1): 1-24.
287. McQuistan, I. B.(1965) Scalar and Vector Fields: A Physical Interpretation (New York: Wiley).
288. Morrison, J. L. (1974) Observed statistical trends in various interpolation algorithms useful for first stage interpolation. Canadian Cartographer, 11 (2): 142-159.
289. Pfalz, J. L. (1976) Surface networks. Geographical Analysis, 8 (1): 77-93.
290. Rana, S., (ed.), (2004) Topological Data Structures for Surfaces (Chichester, England: Wiley).
291. Rhind, D. W. (1971) Automated contouring: an empirical evaluation of some differing techniques. Cartographic Journal, 8: 145-158.
292. Thiessen, A. H. (1911) Precipitation averages for large areas. Monthly Weather Review, 39 (7): 1082-1084.
293. Tobler, W. (1970), A computer movie simulating urban growth in the Detroit region. Proceedings of the I.G.U. Commission on Quantitative Methods. In Economic Geography, 46, Supplement, June 1970
294. Tomlin, D. (1990) Geographical Information Systems and Cartographic Modeling (Englewood Cliffs, NJ: Prentice Hall).
295. Tucker, G. E., Lancaster, S. T., Gasparini, N. M., Bras, R. L., and Rybarczyk, S.M. (2001) An object-oriented framework for distributed hydrologic and geomorphic modeling using triangulated irregular networks. Computers & Geosciences, 27 (8): 959-973.
296. Unwin, D. J. (1981) Introductory Spatial Analysis (London: Methuen).
297. Chilès, J-P. and Delfiner, P. (1999) Geostatistics: Modeling Spatial Uncertainty (New York: Wiley).
298. Cressie, N. (1993) Statistics for Spatial Data (New York: Wiley).
299. Davis, J. C. (2002) Statistics and Data Analysis in Geology (Hoboken, NJ: Wiley).
300. Deutsch, C. V. and Journel, A. G. (1992) GSLIB Geostatistical Software Library and User's Guide (New York: Oxford University Press).
301. Goovaerts, P. (1997) Geostatistics for Natural Resource Evaluation (Oxford and New York: Oxford University Press).
302. Isaaks, E. H. and Srivastava, R. M. (1989) An Introduction to Applied Geostatistics (New York: Oxford University Press).
303. Matheron, G. (1963) Principles of geostatistics. Economic Geology, 58: 1246-1266.
304. Pannatier, Y. (1995) Variowin: Software for Spatial Analysis in 2D (New York: Springer-Verlag).
305. Unwin, D. J. (1975a) Numerical error in a familiar technique: a case study of polynomial trend surface analysis. Geographical Analysis, 7: 197-203.
306. Unwin, D. J. (1975b). An introduction to trend surface analysis. Concepts and Techniques in Modern Geography, 5, 40 pages (Norwich, England: Geo Books). Available at http://www.qmrg.org.uk/catmog.
307. Walvoort, D. J. J. (2004) E(Z)-Kriging: Exploring the World of Ordinary Kriging (Wageningen: Wageningen University &Research Centre). Available at http://www.ai-geostats.org/index.php?id=114.
308. Webster, R. and Oliver, M. (2007). Geostatistics for Environmental Scientists, 2nd ed. (Chichester, England: Wiley).
309. Anselin, L. (1988) Spatial Econometrics: Methods and Models (Dordrecht, The Netherlands: Kluwer).
310. Apan, A. A. and Peterson, J. A. (1998) Probing tropical deforestation: the use of GIS and statistical analysis of georeferenced data. Applied Geography, 18(2): 137-152.
311. Aspinall, R. (1992) An inductive modelling procedure based on Bayes' theorem for analysis of pattern in spatial data. International Journal of Geographical Information Systems, 6(2): 105-121.
312. Bonham-Carter, G. F. (1991) Integration of geoscientific data using GIS. In: M. F. Goodchild, D. W. Rhind, and D. J. Maguire, eds., Geographical Information Systems: Principles and Applications, Vol. 2 (London: Longman), pp. 171-184.
313. Bonham-Carter, G. F. (1995) Geographic Information Systems for Geosciences (Oxford: Pergamon).
314. Burrough, P. (1993) Soil variability: a late 20th century view. Soils & Fertilisers, 56: 529-562.
315. Burrough, P. and Frank, A. U., eds. (1996) Geographical Objects with Uncertain Boundaries (London: Taylor & Francis).
316. Carver, S. J. (1991) Integrating multi-criteria evaluation with GIS. International Journal of Geographical Information Systems, 5(3): 321-339.
317. de Berg, M., van Kreveld, M., Overmars, M., and Schwarzkopf, O. 1997. Computational Geometry: Algorithms and Applications (Berlin and New York: Springer).
318. Douglas, D. (1974) It makes me so CROSS. Harvard University Laboratory for Computer Graphics and Spatial Analysis, Internal memorandum. Reprinted in: Peuquet, D. J., and D. F. Marble (1990) Introductory Resources in Geographic Information Systems (London, England: Taylor and Francis), pp. 303-307.
319. Eastman, J. R. (1999) Multi-criteria evaluation and GIS. In: P. A. Longley, M. F. Goodchild, D. J. Maguire, and D. W. Rhind, eds., Geographical Information Systems, Volume: 1 Principles and Technical Issues (Chichester, England: Wiley), pp. 493-502.
320. Eastman, J. R., Jin, W., Kyem, P. A., and Toledano, J. (1995) Raster procedures for for multi-criteria/multi-objective decisions. Photogrammetric Engineering and Remote Sensing, 61: 539-547.
321. Elwood, S. (2006) Critical issues in participatory GIS: deconstruction, reconstruction and new research directions. Transactions in GIS, 10: 693-708.
322. Fotheringham, A. S., Brunsdon, C., and Charlton, M. (2000) Quantitative Geography: Perspectives on Spatial Data Analysis (London: Sage).
323. Fotheringham, A. S., Brunsdon, C., and Charlton, M. (2002) Geographically Weighted Regression (Chichester, England: Wiley).
324. Franklin, J. (1995) Predictive vegetation mapping: geographic modelling of biospatial patterns in relation to environmental gradients. Progress in Physical Geography, 19(4): 474-499.
325. Gupta, R. P. and Joshi, B. C. (1990) Landslide hazard using the GIS approach-a case study from the Ramganga Catchment, Himalayas. Engineering Geology, 28: 119-145.
326. Hansen, H. S. (2005) GIS-based multi-criteria analysis of wind farm development. In: Hauska, H. and Tueite, H., eds: ScanGIS 2005-Proceedings of the 10th Scandinavian Research Conference on Geographical Information Science (Stockholm: Swedish Department of Planning and Environment), pp. 75-87 (available at also www.scangis.org/scangis2005/papers/hansen.pdf).
327. Harvey, F. (2008) A Primer of GIS: Fundamental Geographic and Cartographic Concepts (New York: Guilford Press).
328. Heuvelink, B. M. and Burrough, P. A. (1993) Error propagation in cartographic modelling using Boolean logic and continuous classification. International Journal of Geographical Information Systems, 7(3): 231-246.
329. Jankowski, P. and Nyerges, T. (2001) Geographic Information Systems for Group Decision Making (London: Taylor & Francis).
330. Jibson, Randall W., and D. K. Keefer (1989) Statistical analysis of factors affecting landslide distribution in the new Madrid seismic zone, Tennessee and Kentucky. Engineering Geology, 27: 509-542.
331. Lee, S., and Choi, J. (2004) Landslide susceptibility mapping using GIS and the weight-of-evidence model. International Journal of Geographical Information Science, 18(8): 789-814.
332. Maling, D. H. (1973) Coordinate Systems and Map Projections (London: George Philip).
333. Malczewski, J. (1999) GIS and Multicriteria Decision Analysis (New York: Wiley).
334. Malczewski, J. (2000) On the use of weighted linear combination method in GIS: common and best practice approaches. Transactions in GIS, 4(1): 5-22.
335. Mather, P. M. (1995) Map-image registration using least-squares polynomials. International Journal of Geographical Information Systems, 9(5): 543-545.
336. McHarg, I. (1969) Design with Nature (New York: Natural History Press).
337. Mertens, B. and Lambin, E. F. (2000) Land-cover-change trajectories in Cameroon. Annals of the Association of American Geographers, 90(3): 467-494.
338. Morad, M., Chalmers, A. I., and O'Regan, P. R. (1996) The role of root-meansquare error in geo-transformation of images in GIS. International Journal of Geographical Information Systems, 10(3): 347-353.
339. Openshaw, S., Carver, S., and Fernie, F. (1989) Britain's Nuclear Waste (London: Pion).
340. Saaty, T. L. (1977) A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15: 234-281.
341. Serneels, S. and Lambin, E. F. (2001) Proximate causes of land-use change in Narok District, Kenya: a spatial statistical model. Agriculture, Ecosystems and Environment, 85: 65-81.
342. Sieber, R. (2006) PPGIS: a literature review and framework. Annals of the Association of American Geographers, 96: 491-507.
343. Sparkes, A. and Kidner, D. (1996) A GIS for the environmental impact assessment of wind Farms. Available at http://proceedings.esri.com/library/userconf/europroc96/PAPERS/PN26/PN26F.HTM.
344. Tomlin, D. (1990) Geographic Information Systems and Cartographic Modeling (Englewood Cliffs, NJ: Prentice Hall).
345. Unwin, D. J. (1995) Geographical information systems and the problem of error and uncertainty. Progress in Human Geography, 19(4): 549-558.
346. Unwin, D. J. (1996) Integration through overlay analysis. In: M. Fischer, H. J. Scholten and D. Unwin, eds., Spatial Analytical Perspectives in GIS (London: Taylor & Francis), pp. 129-138.
347. Unwin, D. J. and Mather, P. M. (1998) Selecting and using ground control points in image rectification and registration. Geographical Systems, 5(3): 239-260.
348. Veregin, H. (1989) Error modelling for the map overlay operation. In: Goodchild, M. F. and Gopal, S., eds., Accuracy of Spatial Databases (London: Taylor & Francis), pp. 3-18.
349. Wang, S. Q. and Unwin, D. J. (1992) Modelling landslide distribution on loess soils in China: an investigation. International Journal of Geographical Information Systems, 6(5): 391-405.
350. Wrigley, N. (1985) Categorical Data Analysis for Geographers and Environmental Scientists (Harlow, England: Longman).
351. Abrahart, R. J. and Openshaw, S., eds. (2000) GeoComputation (London: Taylor & Francis).
352. Allen, P. M. (1997) Cities and Regions as Self-Organizing Systems: Models of Complexity (Amsterdam: Gordon Breach).
353. Anderson, P. W. (1972) More is different: broken symmetry and the nature of the hierarchical structure of science. Science, 177 (4047): 393-396.
354. Armstrong, M. P., Xiao, N., and Bennett, D. A. (2003) Using genetic algorithms to create multicriteria class intervals for choropleth maps. Annals of the Association of American Geographers, 93 (3): 595-623.
355. Bailey, T. C. and Gatrell, A. C. (1995) Interactive Spatial Data Analysis (Harlow, England: Longman).
356. Batty, M. (2001) Polynucleated urban landscapes. Urban Studies, 38(4): 635655.
357. Batty, M., Xie, Y., and Sun, Z. (1999) Modelling urban dynamics through GIS-based cellular automata. Computers, Environment and Urban Systems, 23: 205-233.
358. Beckman, R. J., ed. (1997) The TRansportation ANalysis SIMulation System (TRANSIMS). The Dallas-Ft. Worth Case Study (Los Alamos National Laboratory Unclassified Report LAUR-97-4502LANL).
359. Benenson, I. and Torrens, P. M. (2004) Geosimulation: Automata-based Modeling ofUrban Phenomena (Chichester, England: Wiley).
360. Bian, L. and Liebner, D. (2007) A network model for dispersion of communicable diseases. Transactions in GIS, 11: 155-173.
361. Brookes, C. (1997) A genetic algorithm for locating optimal sites on raster suitability maps. Transactions in GIS, 2: 201-212.
362. Brown, D. G., Page, S., Riolo, R., Zellner, M., and Rand, W. (2005) Path dependence and the validation of agent-based spatial models of land use. International Journal ofGeographical Information Science, 19 (2): 153-174.
363. Byrne, D. (1998) Complexity Theory and the Social Sciences: An Introduction (London: Routledge).
364. Clarke, K. C., Hoppen, S., and Gaydos, L. (1997) A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B: Planning and Design, 24 (2): 247-262.
365. Conley, J. F., Gahegan, M. N., and Macgill, J. (2005) A genetic approach to detecting clusters in point data sets. Geographical Analysis, 37 (3): 286-314.
366. Couclelis, H. (1985) Cellular worlds: a framework for modelling micro-macro dynamics. Environment and Planning A, 17: 585-596.
367. Epstein, J. M. and Axteil, R. (1996) Growing Artificial Societies: Social Science from the Bottom Up (Cambridge, MA: MIT Press).
368. Evans, T. P. and Kelley, H. (2004) Multi-scale analysis of a household level agent-based model of landcover change. Journal of Environmental Management, 72: 57-72.
369. Fischer, M. M. (1994) Expert systems and artificial neural networks for spatial analysis and modelling: essential components for knowledge-based geographical information systems. Geographical Systems, 1: 221-235.
370. Fortnow, L. and Homer, S. (2003) A short history of computational complexity. Bulletin of the European Association for Theoretical Computer Science, 80: 95-133.
371. Fotheringham, S., Brunsdon, C., and Charlton, M. (2000) Quantitative Geography: Perspectives on Spatial Data Analysis (London: Sage).
372. Gahegan, M., German, G., and West, G. (1999) Improving neural network performance on the classification of complex geographic data sets. Journal ofGeographical Systems, 1: 3-22.
373. Gilbert, N. and Troitzsch, K. G. (2005) Simulation for the Social Scientist, 2nd ed. (Buckingham, England: Open University Press).
374. Gimblett, R., ed. (2001) Integrating Geographic Information Systems and Agent-Based Modeling: Techniques for Understanding Social and Ecological Processes (New York: Oxford University Press).
375. Haklay, M., O'Sullivan, D., Thurstain-Goodwin, M., and Schelhorn, T. (2001) ''So go down town'': simulating pedestrian movement in town centres. Environment and Planning B: Planning and Design, 28 (3): 343-359.
376. Harel, D. (2000) Computers Ltd: What They Really Can't Do (Oxford: Oxford University Press).
377. Harrison, S. (1999) The problem with landscape: some philosophical and practical questions. Geography, 84 (4): 355-363.
378. Hartmanis, J. and Stearns, R. (1965) On the computational complexity of algorithms. Transactions ofthe American Mathematical Society, 117: 285-306.
379. Holland, J. H. (1975) Adaptation in Natural and Artificial Systems (Ann Arbor: University of Michigan Press).
380. Itami, R. M. (1994) Simulating spatial dynamics: cellular automata theory. Landscape and Urban Planning, 30(1-2): 27-47.
381. Jepsen, M. R., Leisz, S., Rasmussen, K., Jakobsen, J., Moller-Jensen, L., and Christiansen, L. (2006) Agent-based modelling of shifting cultivation field patterns, Vietnam. International Journal of Geographical Information Science, 20: 1067-1085.
382. Joao, E. (1993) Towards a generalisation machine to minimise generalisation effects within a GIS. In: P. M. Mather, ed., Geographical Information Handling-Research and Applications (Chichester, England: Wiley), pp. 63-78.
383. Kauffman, S. A. (1993) The Origins of Order (Oxford, England: Oxford University Press).
384. Langran, G. (1992) Time in Geographic Information Systems (London: Taylor & Francis).
385. Li, X. and Yeh, A. G.-O. (2000) Modelling sustainable urban development by the integration of constrained cellular automata and GIS. International Journal of Geographical Information Science, 14 (2): 131-152.
386. Longley, P. A., Brooks, S. M., McDonnell, R., and Macmillan, B., eds. (1998) Geocomputation: A Primer (Chichester, England: Wiley).
387. MacGill, J. and Openshaw, S. (1998) The use of flocks to drive a geographic analysis machine. Presented at the Third International Conference on GeoComputation, School of Geographical Science, University of Bristol, England, 17-19 September.
388. Malanson, G. P. (1999) Considering complexity. Annals of the Association of American Geographers, 89 (4): 746-753.
389. Manson, S. M. (2001) Simplifying complexity: a review of complexity theory. Geoforum, 32 (3): 405-414.
390. Manson, S. M. (2006) Land use in the southern Yucatan Peninsular region of Mexico: scenarios of population and institutional change. Computers, Environment and Urban Systems, 30: 230-253.
391. Matheron, G. (1963) Principles of geostatistics. Economic Geology, 58: 1246-1266.
392. McCulloch, W. S. and Pitts, W. (1943) A logical calculus of the ideas immanent in nervous activity. Journal of Mathematical Biophysics, 5: 115-133.
393. Miller, H. J. and Han, J., eds. (2008) Geographic Data Mining and Knowledge Discovery, 2nd ed. (London: Taylor & Francis).
394. Naylor, C. (1983) Build Your Own Expert System (Bristol, England: Sigma).
395. O'Brien, J., and Gahegan, M. N. (2004) Knowledge framework for representing, manipulating, and reasoning with geographic semantics. In: Z. Li, Q. Zhou, and W. Kainz, eds., Advances in Spatial Analysis and Decision Making (Lisse, The Netherlands: Swetz & Zeitlinger), pp. 31-44.
396. Openshaw, S. (1993), Exploratory space-time-attribute pattern analysers. In: A. S. Fotheringham and P. Rogerson, eds., Spatial Analysis and GIS (London: Taylor & Francis), pp. 147-163.
397. Openshaw, S., Charlton, M., Wymer, C., and Craft, A. (1987) Developing a mark 1 Geographical Analysis Machine for the automated analysis ofpoint data sets. International Journal ofGeographical Information Systems, 1: 335-358.
398. Openshaw S. and Openshaw, C. (1997) Artificial Intelligence in Geography (Chi-chester, England: Wiley).
399. O'Sullivan, D. (2001) Graph-cellular automata: a generalised discrete urban and regional model. Environment and Planning B: Planning and Design, 28 (5): 687-705.
400. O'Sullivan, D. (2004) Complexity science and human geography. Transactions of the Institute ofBritish Geographers, 29 (3): 282-295.
401. O'Sullivan, D. (2005) Geographical information science: time changes everything. Progress in Human Geography, 29 (6): 749-756.
402. O'Sullivan, D. (2008) Geographical information science: agent-based models. Progress in Human Geography, 32 (2): 541-550.
403. Parker, D. C, Manson, S. M., Janssen, M. A., Hoffmann, M. J., and Deadman, P. (2003) Multiagent systems for the simulation of land-use and land-cover change: a review. Annals of the Association of American Geographers, 93: 316-340.
404. Phillips, J. D. (1999) Spatial analysis in physical geography and the challenge; of deterministic uncertainty. Geographical Analysis, 31 (4): 359-372.
405. Portugali, J. (2000) Self-Organisation and the City (Berlin: Springer-Verlag).
406. Poundstone, W. (1985) The Recursive Universe (New York: Morrow).
407. Prigogine, I., and Stengers, I. (1985) Order out of Chaos: Man's New Dialogue with Nature (London, England: Fontana Press).
408. Resnick, M. (1994) Turtles, Termites, and Traffic Jams (Cambridge, MA: MIT Press).
409. Ripley, B. D. (1976) The second-order analysis of stationary point processes. Journal of Applied Probability, 13: 255-266.
410. Rodrigues, A. and Raper, J. (1999) Defining spatial agents. In A. S. Camara and J. Raper, eds., Spatial Multimedia and Virtual Reality (London: Taylor & Francis), pp. 111-129.
411. Sayer, A. (1992) Method in Social Science: A Realist Approach (London: Routledge).
412. Smith, T., Peuquet, D., Menon, S., and Agarwal, P. (1987) KBGIS-II: a knowledge based geographical information system. International Journal of Geographical Information Systems, 1: 149-172.
413. Takeyama, M. (1997) Building spatial models within GIS through Geo-Algebra. Transactions in GIS, 2: 245-256.
414. Thomas, M. (1949) A generalisation of Poisson's binomial limit for use in ecology. Biometrika, 36: 18-25.
415. Toroczkai, Z., and Guclu, H. (2007) Proximity networks and epidemics, Physica A: Statistical Mechanics and Its Applications, 378: 68-75.
416. Wadge, G., Wislocki, A., and Pearson, E. J. (1993) Mapping natural hazards with spatial modelling systems. In P. Mather, ed., Geographic Information Handling-Research and Applications (Chichester, England: Wiley), pp. 239-250.
417. Waldrop, M. (1992) Complexity: The Emerging Science at the Edge of Chaos (New York: Simon and Schuster).
418. Ward, D. P., Murray, A. T., and Phinn, S. R. (2000) A stochastically constrained cellular model ofurban growth. Computers, Environment and Urban Systems, 24: 539-558.
419. Weaver, W. (1948) Science and complexity. American Scientist, 36: 536-544.
420. Webster, R. and Oliver, M. A. (2007) Geostatistics for Environmental Scientists, 2nd ed. (Chichester, England: Wiley).
421. Wesseling, C. G., Karssenberg, D., Van Deursen, W., and Burrough, P.A. (1996) Integrating dynamic environmental models in GIS: the development of a Dynamic Modelling language. Transactions in GIS, 1: 40-48.
422. Westervelt, J. O. and Hopkins, L. D. (1999) Modeling mobile individuals in dynamic landscapes. International Journal of Geographical Information Science, 13 (3): 191-208.
423. White, R. and Engelen, G. (2000) High-resolution integrated modelling of the spatial dynamics of urban and regional systems. Computers, Environment and Urban Systems, 24: 383-400.
424. Wilson, A. G. (2000) Complex Spatial Systems: The Modelling Foundations of Urban and Regional Analysis (Harlow, England: Prentice Hall/Pearson Education).
425. Youden, W. J. and Mehlich, A. (1937) Selection of efficient methods for soil sampling, Contributions of the Boyce Thompson Institute for Plant Research,9: 59-70.
426. Strang, G. (1988) Linear Algebra and Its Applications, 3rd ed., ( Fort Worth, TX: Harcourt Brace Jovanovich).