Testing popular visualization techniques for representing model uncertainty

Cartography and Geographic Information Science

Volumn 30, Issue 3, 2003, Pages 249-261

  Aerts, Jeroen C J H ^a   Clarke, Keith C ^b   Keuper, Alex D ^b  

^a INSTITUTE FOR ENVIRONMENTAL STUDIES   (Netherlands)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATABASE SYSTEMS; DECISION MAKING; DECISION SUPPORT SYSTEMS; URBAN PLANNING;

LANDUSE PLANNING;

GEOGRAPHIC INFORMATION SYSTEMS;

DECISION SUPPORT SYSTEM; UNCERTAINTY ANALYSIS; URBAN PLANNING; VISUALIZATION;

EID: 0142197810     PISSN: 15230406     EISSN: None     Source Type: Journal    
DOI: 10.1559/152304003100011180     Document Type: Article

References (45)

1. Aerts, J.C.J.H., and G.B.M. Heuvelink. 2002. Using simulated annealing for resource allocation. International Journal of GIS 16(6): 571-87.
2. Aerts, J.C.J.H. 2002. Spatial decision support for resource allocation. Integration of optimization, uncertainty analysis and visualization techniques. Dissertation, University of Amsterdam. Amsterdam, The Netherlands: Thela Thesis publishers.
3. Armstrong, M.P., P.J. Densham, P. Lolonis, and G. Rushton. 1992. Cartographic displays to support locational decision making. Cartography and Geographic Information Systems 19(3): 154-64.
4. Bastin, L., J. Wood, and P.F. Fischer. 2000. Visualising uncertainty in fuzzy thematic classifications of multispectral satellite imagery. In: W. Shi, M.F. Goodchild, and P.F. Fisher (eds), International Symposium on Spatial Data Quality, Hong Kong. pp. 243-52.
5. Beard, M.K., and B.P. Buttenfield. 1991. Visualization of spatial data quality. Scientific Report for the Specialist Meeting June 1991. NCGIA Technical Paper 91-26, Santa Barbara, California.
6. Beard, M.K., and B.P. Buttenfield. 1999. Detecting and evaluating errors by graphical methods. In: P.A.Longley, M.F. Goodchild, D.J. Maguire, and D.W. Rhind (eds), Geographic information systems. pp. 219-33.
7. Bertin, J. 1983. Semiology of graphics. Madison, Wisconsin: The University of Wisconsin Press.
8. Brewer, C.A. 1999a. Color use guidelines for mapping and visualization. [http://www.personal.psu.edu/faculty/c/a/cab38/ColorSchHome.html. Last visited June 2003)].
9. Brewer, C. A. 1999b. Color use guidelines for data representation. Proceedings of the Section on Statistical Graphics. American Statistical Association, Alexandria, Virginia. pp. 55-60.
10. Buttenfield, B., and M.K. Beard. 1994. Graphical and geographical components of data quality. In: H. M.Hernshaw and D. J. Unwin (eds). Visualization in geographical information systems. New York, New York: J. Wiley, pp. 150-7.
11. Candau, J., S. Rasmussen, and K.C. Clarke. 2000. A coupled cellular automaton model for land use/land cover dynamics. GIS/EM4 Conference, Banff Alberta 2000. [http://www.Colorado.EDU/research/cires/banff/pubpapers/94/. Last visited June 2003)].
12. Clarke, K.C., and L.J. Gaydos. 1998. Loose-coupling a cellular automaton model and GIS: Long-term urban growth prediction for San Francisco and Washington/ Baltimore. International Journal of Geographical Information Science 12(7): 699-714.
13. Clarke, K.C., P.D. Teague, and H.G. Smith. 2000. Virtual depth-based representation of cartographic uncertainty. In: W. Shi, M.F. Goodchild, and P.F. Fisher (eds), International Symposium on Spatial Data Quality, Hong Kong. pp. 253-9.
14. Cleaves, D.A. 1995. Assessing and communicating uncertainty in decision support systems: Lessons from an ecosystem policy analysis. Al Applications 9(3): 87-102.
15. Crossland, M.D., B.E. Wynne, and W.C. Perkins. 1995. Spatial decision support systems: An overview of technology and a test of efficacy. Decision Support System 14: 219-35.
16. Davis, T.J., and C.P. Keller. 1997. Modelling and visualizing multiple spatial uncertainties. Computers and Geosciences 23(4): 397-408.
17. Drecki, I. 2000. Visualizing of uncertainty in geographic data. In: W. Shi, M.F. Goodchild, and P.F. Fisher (eds), International Symposium on Spatial Data Quality. Hong Kong, pp. 260-71.
18. Ehlschlaeger, Ch.R. 2002. Representing multiple spatial statistics in generalized elevation uncertainty models: Moving beyond the variogram. International Journal of Geographic Information Science 16(3): 259-85.
19. Ehlschlaeger, Ch.R., A.M. Shortridge, and M.F. Goodchild. 1997. Visualizing spatial data uncertainty using animation. Computers and Geosciences 23(4): 387-395.
20. Ehlschlaeger, Ch.R., and M.F. Goodchild. 1994. Uncertainty in spatial data: Defining, visualizing and managing data errors. Proceedings of GIS/LIS, Phoenix, Arizona. pp. 246-53.
21. Evans, B.J. 1997. Dynamic display of spatial data reliability: Does it benefit the map user? Computers & Geosciences 23(4): 409-22.
22. Fisher, P.F. 1994. Visualization of the reliability in classified remotely sensed images. Photogrammetric Engineering and Remote Sensing 60: 905-10.
23. nd ed. Newbury Park, California: Sage.
24. Goodchild, M.F., B. Buttenfield, and J. Wood. 1994. Introduction to visualizing data validity. In: H. M. Hernshaw, , and D. J. Unwin (eds), Visualization in geographical information systems. New York, New York: J. Wiley. pp. 141-9.
25. Grabaum, R., and B.C. Meyer. 1998. Multi criteria optimization of landscapes using GIS-based functional assessments. Landscape and Urban Planning 43: 21-34.
26. Heuvelink, G.B.M. 1998. Error propagation in environmental modeling with GIS. London, U.K.: Taylor & Francis.
27. Hunter, G.J., and M.F. Goodchild. 1995. Dealing with error in spatial databases: A simple case study. Photogrammetric Engineering & Remote Sensing 61(5): 529-37.
28. Hunter, G.J. 1999. Managing uncertainty in GIS. In: P.A. Longley, M.F. Goodchild, D.J. Maguire, and D.W. Rhind (eds), Geographic information systems. New York, New York: J. Wiley. pp. 633-41.
29. Kraak, M.J. 1999. Visualising spatial distributions. In: P.A. Longley, M.F. Goodchild, D.J. Maguire, and D.W. Rhind (eds), Geographic information systems. New York, New York: J. Wiley. pp. 157-73.
30. Leitner, M., and B.P. Buttenfield 1997. Cartographic guidelines for visualizing attribute accuracy. Proceedings, AUTO-CARTO 13, Seattle, Washington. Pp. 184-94.
31. Leitner M., and B.P. Buttenfield. 2000. Guidelines for the display of attribute certainty. Cartography and Geographic Information Science 27(1): 3-14.
32. MacEachren, A.M. 1992. Visualizing uncertain information. Cartographic Perspective 13: 10-19.
33. MacEachren, A.M. 1994. Some truth with maps: A primer on symbolization & design. Association of American Geographers, Washington, D.C.
34. MacEachren, A.M., and M.J. Kraak. 1997. Exploratory cartographic visualization: Advancing the agenda. Computers & Geosciences 23(4): 335-43.
35. MacEachren, A.M., M. Wachowicz, R. Edsall, and R. Masters. 1999. Constructing knowledge from multivariate spatiotemporal data: Integrating geographical visualization with knowledge discovery in database methods. International Journal of Geographical Information Science 13(4): 311-34.
36. Nedovic-Budic,Z. 1999. Geographic information science implications for urban and regional planning. URISA Journal 12(2): 81-93.
37. Pang, A.T., C.M. Wittenbrink, and S. Lodha. 1997. Approaches to uncertainty visualization. The Visual Computer 13: 370-90.
38. Paoli, G., and B. Bass. 1997. Editorial: Climate change and variability, uncertainty and decision making. Journal of Environmental Management 49(1): 1-6.
39. Rosenthal, R., and R. Rosnow. 1991. Essentials of behavioral research: Methods and data analysis. New York, New York: McGraw-Hill.
40. SBC (Santa Barbara County). 2000. Santa Barbara County 2030 land and population. Planning and Development Division. [http://www.co.santabarbara.ca.us/plandev/. (Last visited June 2003)].
41. Schatten, A. 1999. Cellular automata, digital worlds. [http://www.ifs.tuwien.ac.at/~aschatt/info/ca/ca.html. Last visited June 2003)].
42. Silva, E.A., and K.C. Clarke. 2001. Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal. Computers, Environment and Urban Systems 26(6): 525-52.
43. Van der Wel, F.J.M., R.M. Hootsmans, and F. Ormeling. 1994. Visualization of data quality. In: A.M. MacEachren and D.R. Fraser Taylor (eds), Visualization in modern cartography. New York, New York: Elsevier Scientific.
44. Van der Wel, F.J.M, and L.C. Van der Gaag. 1998. Visual exploration of uncertainty in remote sensing classification. Computers & Geosciences 24(4): 335-43.
45. Watkins, E.T. 2000. Improving the analyst and decision-makers perspective through uncertainty visualization. Thesis AFIT/GCS/ENG/00M-24. Department of the Air Force Air University. Air force Institute of Technology, Wright Patterson Air Force Base, Ohio. (Last visited June 2003)]. http://www.au.af.mil/au/database/research/ ay2000/afit-gcs-eng-00m-24.htm