Visualization of uncertainty associated with spatial prediction of continuous variables using HSI color model: a case study of prediction of pH for topsoil in peri-urban Beijing, China

Man-zhi Tan , Jie Chen

Journal of Forestry Research ›› 2008, Vol. 19 ›› Issue (4) : 319 -322.

PDF
Journal of Forestry Research ›› 2008, Vol. 19 ›› Issue (4) : 319 -322. DOI: 10.1007/s11676-008-0058-8
Research Paper

Visualization of uncertainty associated with spatial prediction of continuous variables using HSI color model: a case study of prediction of pH for topsoil in peri-urban Beijing, China

Author information +
History +
PDF

Abstract

Hue-Saturation-Intensity (HSI) color model, a psychologically appealing color model, was employed to visualize uncertainty represented by relative prediction error based on the case of spatial prediction of pH of topsoil in the peri-urban Beijing. A two-dimensional legend was designed to accompany the visualization—vertical axis (hues) for visualizing the predicted values and horizontal axis (whiteness) for visualizing the prediction error. Moreover, different ways of visualizing uncertainty were briefly reviewed in this paper. This case study indicated that visualization of both predictions and prediction uncertainty offered a possibility to enhance visual exploration of the data uncertainty and to compare different prediction methods or predictions of totally different variables. The whitish region of the visualization map can be simply interpreted as unsatisfactory prediction results, where may need additional samples or more suitable prediction models for a better prediction results.

Keywords

Hue-Saturation-Intensity / color model / spatial prediction / uncertainty / visualization

Cite this article

Download citation ▾
Man-zhi Tan, Jie Chen. Visualization of uncertainty associated with spatial prediction of continuous variables using HSI color model: a case study of prediction of pH for topsoil in peri-urban Beijing, China. Journal of Forestry Research, 2008, 19(4): 319-322 DOI:10.1007/s11676-008-0058-8

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Dutton G. 1992. Handling positional uncertainty in spatial databases. In Proceedings of 5th International Symposium on Spatial Data Handling. University of South Carolina, August 1992, pp460–469.

[2]

Goovaerts P. Geo-statistical modeling of uncertainty in soil science Geoderma, 2001, 103: 3-26.

[3]

Goovaerts P., Journel A.G. Integrating soil map information in modeling the spatial variation of continuous soil properties Eur J Soil Sci, 1995, 46: 397-414.

[4]

Hengl T., Heuvelink G.B.M., Stein A. A generic framework for spatial prediction of soil variables based on regression-kringing Geoderma, 2004, 120: 75-93.

[5]

Hengl T. Visualisation of uncertainty using the HSI colour model: computations with colours 7th International Conference on Geo-Computation (CD-ROM), 2003 Southampton: University of Southampton 8

[6]

Jiang B. Fuzzy overlay analysis and visualization in geographic information systems, 1996 Utrecht: University of Utrecht

[7]

Li Y., Shi Z., Wang R., Huang M. Estimates of electrical conductivity for coastal saline soil profile using cokriging under different sampling density Acta Pedological Sinica, 2004, 41(3): 434-443.

[8]

Mowrer H.T., Congalton R.G. Quantifying spatial uncertainty in natural resources: theory and applications for GIS and remote sensing, 2000 Hannover: Ann Arbor Press 350

[9]

Maceachren A.M. Visualizing uncertain information Cartographic Perspective, 1992, 13: 10-19.

[10]

Monmonier M. Strategies for the interactive exploration of geographic correlation Proceedings of the 4th International Symposium on Spatial Data Handling, 1990, 1: 512-521.

[11]

Park S., Vlek P. Environmental correlation of three-dimensional soil spatial variability: a comparison of three adaptive techniques Geoderma, 2002, 109(1–2): 117-140.

[12]

Pang A, Furman J, Nuss W. 1994. Data quality issues in visualization. In: Robert J. et al. (eds), SPIE Vol. 2178 Visual Data Exploration and Analysis, p12–23. SPIE, February 1994.

[13]

Smith J.L., Halvorson J.J., Papendick R.I. Using multiple-variable indicator kriging for evaluating soil quality Soil Sci Soc Am J, 1993, 57: 743-749.

[14]

Webster R., Oliver M.A. Optimal interpolation and isarithmic mapping of soil properties: VI. Disjunctive kriging and mapping the conditional probability J Soil Sci, 1989, 40: 497-512.

AI Summary AI Mindmap
PDF

121

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/