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Proceedings Paper

Visualizing the uncertainty of geo-information from Landsat ETM+ imagery by fuzzy reasoning
Author(s): Ping Wang; Fang Huang; Xiangnan Liu
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Paper Abstract

Uncertainty is one important feature of spatial information quality and attracting much more attentions recently. The visualization is an effective way to express the magnitude, pattern and propagation of the uncertainty. In this paper, the visualization method of geospatial information uncertainty in Landsat ETM+ imagery is put forward and described. Firstly, an improved fuzzy reasoning classification method is proposed, and farmland and grassland information are extracted from the ETM+ imagery respectively based on the algorithm. Then the uncertainty of the classification is analyzed, measured and visualized supported by GIS. The uncertainty can be expressed and visualized by different spatial distribution range of cropland and grassland when adjusting their membership values setting. The uncertainty threshold supplies a visual cognition for data users to know the data quality better and make full use of the data more correctly. At the same time, aiming at the overlay areas with similar membership values, other ancillary information can help to improve the classification accuracy and conquer the difficulties in distinguishing cropland from grassland in Landsat ETM+.

Paper Details

Date Published: 8 August 2007
PDF: 9 pages
Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 67520L (8 August 2007); doi: 10.1117/12.760446
Show Author Affiliations
Ping Wang, Northeast Normal Univ. (China)
Fang Huang, Northeast Normal Univ. (China)
Xiangnan Liu, China Univ. of Geosciences (China)

Published in SPIE Proceedings Vol. 6752:
Geoinformatics 2007: Remotely Sensed Data and Information

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