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Exploring uncertaintly in remotely sensed data with parallel coordinate plots
Citation
Yong, G and Sanping, L and Lakhan, C and Lucieer, A, Exploring uncertaintly in remotely sensed data with parallel coordinate plots, International Journal of Applied Earth Observation and Geoinformation, 11, (6) pp. 413-422. ISSN 1569-8432 (2009) [Refereed Article]
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DOI: doi:10.1016/j.jag.2009.08.004
Abstract
The existence of uncertainty in classified remotely sensed data necessitates the application of enhanced techniques for identifying and visualizing the various degrees of uncertainty. This paper, therefore, applies the multidimensional graphical data analysis technique of parallel coordinate plots (PCP) to visualize the uncertainty in Landsat Thematic Mapper (TM) data classified by the Maximum Likelihood Classifier (MLC) and Fuzzy C-Means (FCM). The Landsat TM data are from the Yellow River Delta, Shandong Province, China. Image classification with MLC and FCM provides the probability vector and
fuzzymembership vector of each pixel. Based on these vectors, the Shannon’s entropy (S.E.) of each pixel is calculated. PCPs are then produced for each classification output. The PCP axes denote the posterior probability vector and fuzzy membership vector and two additional axes represent S.E. and the
associated degree of uncertainty. The PCPs highlight the distribution of probability values of different land cover types for each pixel, and also reflect the status of pixels with different degrees of uncertainty.
Brushing functionality is then added to PCP visualization in order to highlight selected pixels of interest.
This not only reduces the visualization uncertainty, but also provides invaluable information on the positional and spectral characteristics of targeted pixels.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | Parallel coordinate plots (PCP), remotely sensed data, Shannon's entropy, Uncertainty, Interactive visualisation, Brushing |
| Research Division: | Engineering |
| Research Group: | Geomatic engineering |
| Research Field: | Photogrammetry and remote sensing |
| Objective Division: | Environmental Management |
| Objective Group: | Other environmental management |
| Objective Field: | Other environmental management not elsewhere classified |
| UTAS Author: | Lucieer, A (Professor Arko Lucieer) |
| ID Code: | 60304 |
| Year Published: | 2009 |
| Web of Science® Times Cited: | 14 |
| Deposited By: | Geography and Environmental Studies |
| Deposited On: | 2010-01-29 |
| Last Modified: | 2010-04-14 |
| Downloads: | 0 |
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