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A Case-based Reasoning Approach to Fuzzy Soil Mapping

Xun Shi*,a, A-Xing Zhub,c, James E. Burtc, Feng Qic and Duane Simonsond

a Dep. of Geography, Dartmouth College, 6017 Fairchild, Hanover, NH 03755
b State Key Lab of Resources and Environmental Information Systems, Inst. of Geographical Sciences and Natural Resources Res., Chinese Academy of Sciences, Building 917, Datun Road, An Wai, Beijing 100101, China
c Dep. of Geography, University of Wisconsin-Madison, 550 North Park Street, Madison, WI 53706
d NRCS-USDA, 1850 Bohmann Drive, Suite C, Richland Center, WI 53581



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Fig. 1. Location of the study area.

 


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Fig. 2. Topography of the Pleasant Valley study area, Wisconsin.

 


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Fig. 3. Procedure of creating tacit points (cases) using 3dMapper.

 


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Fig. 4. (left) Map of depth to C horizon of the Pleasant Valley study area, based on the CBR result. (right) Map of depth to C horizon of the Pleasant Valley study area, based on the soil survey map.

 


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Fig. 5. (a) Scatter plot of observed depths to C horizon vs. the depth to C horizon derived from the case-based reasoning result at 59 sample locations in the Pleasant Valley study area. (b) Scatter plot of observed depth to C horizon vs. the depth to C horizon derived from the soil survey map at 59 sample locations in the Pleasant Valley study area.

 


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Fig. 6. (left) Sand percentage in A horizon derived from the case-based reasoning result. (right) Sand percentage in A horizon derived from the soil survey map.

 


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Fig. 7. (left) Silt percentage in A horizon derived from the case-based reasoning result. (right) Silt percentage in A horizon derived from the soil survey map.

 





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