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Integration of Kriging Algorithm and Remote Sensing Data and Uncertainty Analysis for Environmental Thematic Mapping: A Case Study of Sediment Grain Size Mapping  

Park, No-Wook (Dept. of Geoinformatic Engineering, Inha University)
Jang, Dong-Ho (Dept. of Geography, Kongju National University)
Publication Information
Journal of the Korean Geographical Society / v.44, no.3, 2009 , pp. 395-409 More about this Journal
Abstract
The objective of this paper is to illustrate that kriging can provide an effective framework both for integrating remote sensing data and for uncertainty modeling through a case study of sediment grain size mapping with remote sensing data. Landsat TM data which show reasonable relationships with grain size values are used as secondary information for sediment grain size mapping near the eastern part of Anmyeondo and Cheonsuman bay. The case study results showed that uncertainty attached to prediction at unsampled locations was significantly reduced by integrating remote sensing data through the analysis of conditional variance from conditional cumulative distribution functions. It is expected that the kriging-based approach presented in this paper would be efficient integration and analysis methodologies for any environmental thematic mapping using secondary information as well as sediment grain size mapping.
Keywords
kriging; multi-Gaussian approach; CCDF; uncertainty;
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Times Cited By KSCI : 5  (Citation Analysis)
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