Comparison of grouping and the quality of legacy soil map boundaries with numerical data mining models: a case study of some regions of Chaharmahal-va-Bakhtiari province

Document Type : Original Article

Authors

1 Soil Science Department, Agriculture faculty, Shahrekord University

2 Soil science department, Agriculture faculty, Shahid Bahonar University

Abstract

Investigation of the the relationship between soils and grouping them based on different factors, plays an important role in different fields and aspects such as land management and sustainable agriculture. This launched by creating subjective or mental models and using environmental factors in the format of traditional soil maps. It afterward continued by relying on distance and similarity measurement through quantitative or mathematical models. This study aims to compare soil groups in soil maps with classical and modern models. For this purpose, legacy soil data of a map of Shahrekord-Borujen in Chaharmahal-va-Bakhtiari province is classified by using various algorithms: Heretical clustering, k-means, classification tree, and taxonomic distance. Soil groups gained from these numerical methods were then compared with soil groups in the legacy maps. Results of investigations in 90m spatial resolution showed that the classes from the decision tree were more in line with the legacy soil classes. The hierarchical clustering and k-means also resulted in group compositions similar to those of the legacy maps in terms of soil environmental and morphological characteristics that follow the traditional photographic units. The taxonomic distance led to the best combination of soil classes in the term of their traits with the highest within-class correlation (0.522) and the least within-group variance to between-group variance ratio. Low p < /em>-values in multivariate analysis of variance (MANOVA) between 0.001 in the traditional model up to 0.014 in the tree model showed that the models used in this study have effectively separated soils, except for K-means. Overall, findings show that using numerical classification models can discover the quantitative relations between soils. The surveyor can afterward modify the composition of soil classes considering his experience and knowledge of the study area in order to achieve more homogenous soil groups in terms of their management and taxonomic characteristics.

Keywords

References

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History

  • Receive Date: 29 September 2019
  • Revise Date: 16 January 2021
  • Accept Date: 13 January 2020

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