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Application of random sets to model uncertainties of natural entities extracted from remote sensing images

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Abstract

Remotely sensed images as a major data source to observe the earth, have been extensively integrated into spatial-temporal analysis in environmental research. Information on spatial distribution and spatial-temporal dynamic of natural entities recorded by series of images, however, usually bears various kinds of uncertainties. To deepen our insight into the uncertainties that are inherent in these observations of natural phenomena from images, a general data modeling methodology is developed to embrace different kinds of uncertainties. The aim of this paper is to propose a random set method for uncertainty modeling of spatial objects extracted from images in environmental study. Basic concepts of random set theory are introduced and primary random spatial data types are defined based on them. The method has been applied to dynamic wetland monitoring in the Poyang Lake national nature reserve in China. Four Landsat images have been used to monitor grassland and vegetation patches. Their broad gradual boundaries are represented by random sets, and their statistical mean and median are estimated. Random sets are well suited to estimate these boundaries. We conclude that our method based on random set theory has a potential to serve as a general framework in uncertainty modeling and is applicable in a spatial environmental analysis.

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Acknowledgments

This work was carried out in International Institute for Geo-Information Science and Earth Observation (ITC), with the support of ITC PhD fund. It is also partially funded by the 973 Program (Grant No. 2009CB723905), Sino-Germany Joint Project (Grant No. 2006DFB91920), National Key Project of Scientific and Technical Supporting Programs (2007BAC23B05) and NSFC project (Grant No. 40721001). The authors would like to express their many thanks to Dr. Marie-Colette van Lieshout and two anonymous reviewers for their valuable comments.

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Authors and Affiliations

  1. Earth Observation Science Department, International Institute for Geo-Information Science and Earth Observation (ITC), Hengelosestraat 99, 7500 AA, Enschede, The Netherlands

    Xi Zhao & Alfred Stein

  2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Luo Yu Road 129, Wuhan, 430079, China

    Xi Zhao & Xiaoling Chen

  3. The Key Laboratory of Poyang Lake Wetland and Watershed Research, Jiangxi Normal University, Ziyang Road 99, Nanchang, China

    Xiaoling Chen

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  1. Xi Zhao
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  2. Alfred Stein
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  3. Xiaoling Chen
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Correspondence to Xi Zhao.

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Zhao, X., Stein, A. & Chen, X. Application of random sets to model uncertainties of natural entities extracted from remote sensing images. Stoch Environ Res Risk Assess 24, 713–723 (2010). https://doi.org/10.1007/s00477-009-0358-3

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