UWSpace >
University of Waterloo >
Electronic Theses and Dissertations (UW) >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10012/6715

Title: Fuzzy logic-based digital soil mapping in the Laurel Creek Conservation Area, Waterloo, Ontario
Authors: Ren, Que
Keywords: digital soil mapping
FCM clustering
Approved Date: 9-May-2012
Date Submitted: 2012
Abstract: The aim of this thesis was to examine environmental covariate-related issues, the resolution dependency, the contribution of vegetation covariates, and the use of LiDAR data, in the purposive sampling design for fuzzy logic-based digital soil mapping. In this design fuzzy c-means (FCM) clustering of environmental covariates was employed to determine proper sampling sites and assist soil survey and inference. Two subsets of the Laurel Creek Conservation area were examined for the purposes of exploring the resolution and vegetation issues, respectively. Both conventional and LiDAR-derived digital elevation models (DEMs) were used to derive terrain covariates, and a vegetation index calculated from remotely sensed data was employed as a vegetation covariate. A basic field survey was conducted in the study area. A validation experiment was performed in another area. The results show that the choices of optimal numbers of clusters shift with resolution aggregated, which leads to the variations in the optimal partition of environmental covariates space and the purposive sampling design. Combining vegetation covariates with terrain covariates produces different results from the use of only terrain covariates. The level of resolution dependency and the influence of adding vegetation covariates vary with DEM source. This study suggests that DEM resolution, vegetation, and DEM source bear significance to the purposive sampling design for fuzzy logic-based digital soil mapping. The interpretation of fuzzy membership values at sampled sites also indicates the associations between fuzzy clusters and soil series, which lends promise to the applicability of fuzzy logic-based digital soil mapping in areas where fieldwork and data are limited.
Program: Geography
Department: Geography
Degree: Master of Science
URI: http://hdl.handle.net/10012/6715
Appears in Collections:Faculty of Environment Theses and Dissertations
Electronic Theses and Dissertations (UW)

Files in This Item:

File Description SizeFormat
Ren_Que.pdf5.42 MBAdobe PDFView/Open


This item is protected by original copyright

All items in UWSpace are protected by copyright, with all rights reserved.

 

University of Waterloo Library
200 University Avenue West
Waterloo, Ontario, Canada N2L 3G1
519 888 4883

contact us | give us feedback | http://www.lib.uwaterloo.ca | © 2006 University of Waterloo