Omuto CT. 2012. DSM for mapping soil classes in Somalia. In Vargas et al. Workshop Proceedings for "GSP / e-SOTER Workshop: Towards Global Soil Information: Activities within the GEO Task Global Soil Data". 20-23 March 2012. FAO. Rome

Citation:
THINE DROMUTOCHRISTIAN. "Omuto CT. 2012. DSM for mapping soil classes in Somalia. In Vargas et al. Workshop Proceedings for "GSP / e-SOTER Workshop: Towards Global Soil Information: Activities within the GEO Task Global Soil Data". 20-23 March 2012. FAO. Rome.". In: SR-CRSP Technical Report Series No. 43 pp. 64. (Co-authored with Rex Campbell and Herbert Lionberger). FAO; 2012.

Abstract:

Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Soil occurs in nature in groups with unique response characteristics to its forming factors. These characteristics should ideally be represented as a family of curves in the models for producing soil maps. However, the current approaches for producing soil maps use a single model which either blocks/controls the grouping effects or do not statistically recognize the natural landscape groupings. This study tested mixed-effects modelling technique for ingenious recognition of soil groupings and consequent improvement of the accuracy of the resultant soil maps. Mixed-effects modelling is a form of regression analysis for simultaneous modelling of the average landscape characteristics and individual groups within the landscape. It can model a family of curves and potentially remove inadequacies inherent in the current models for soil mapping. Its potential in regression kriging of continuous and categorical soil attributes has been shown in this paper, where it produced about 60% accuracy with holdout validation. Compared to the current application of a single model in regression kriging, mixed-effects modelling produced about five times improvement of the mapping accuracy. It is anticipated that its adoption will contribute to improved soil mapping

Notes:

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