Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1016/j.geomorph.2017.02.015 |
Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran | |
Zeraatpisheh, Mojtaba1,3; Ayoubi, Shamsollah1; Jafari, Azam2; Finke, Peter3 | |
通讯作者 | Ayoubi, Shamsollah |
来源期刊 | GEOMORPHOLOGY
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ISSN | 0169-555X |
EISSN | 1872-695X |
出版年 | 2017 |
卷号 | 285页码:186-204 |
英文摘要 | The efficiency of different digital and conventional soil mapping approaches to produce categorical maps of soil types is determined by cost, sample size, accuracy and the selected taxonomic level. The efficiency of digital and conventional soil mapping approaches was examined in the semi-arid region of Borujen, central Iran. This research aimed to (i) compare two digital soil mapping approaches including Multinomial logistic regression and random forest, with the conventional soil mapping approach at four soil taxonomic levels (order, suborder, great group and subgroup levels), (ii) validate the predicted soil maps by the same validation data set to determine the best method for producing the soil maps, and (iii) select the best soil taxonomic level by different approaches at three sample sizes (100, 80, and 60 point observations), in two scenarios with and without a geomorphology map as a spatial covariate. In most predicted maps, using both digital soil mapping approaches, the best results were obtained using the combination of terrain attributes and the geomorphology map, although differences between the scenarios with and without the geomorphology map were not significant. Employing the geomorphology map increased map purity and the Kappa index, and led to a decrease in the ’noisiness’ of soil maps. Multinomial logistic regression had better performance at higher taxonomic levels (order and suborder levels); however, random forest showed better performance at lower taxonomic levels (great group and sub, group levels). Multinomial logistic regression was less sensitive than random forest to a decrease in the number of training observations. The conventional soil mapping method produced a map with larger minimum polygon size because of traditional cartographic criteria used to make the geological map 1:100,000 (on which the conventional soil mapping map was largely based). Likewise, conventional soil mapping map had also a larger average polygon size that resulted in a lower level of detail. Multinomial logistic regression at the order level (map purity of 0.80), random forest at the suborder (map purity of 0.72) and great group level (map purity of 0.60), and conventional soil mapping at the subgroup level (map purity of 0.48) produced the most accurate maps in the study area. The multinomial logistic regression method was identified as the most effective approach based on a combined index of map purity, map information content, and map production cost. The combined index also showed that smaller sample size led to a preference for the order level, while a larger sample size led to a preference for the great group level. (C) 2017 Elsevier B.V. All rights reserved. |
英文关键词 | Digital soil mapping Conventional soil mapping Map purity Modelling efficiency Multinomial logistic regression Random forest |
类型 | Article |
语种 | 英语 |
国家 | Iran ; Belgium |
收录类别 | SCI-E |
WOS记录号 | WOS:000405048500013 |
WOS关键词 | RANDOM FORESTS ; CLASSIFICATION ; MAP ; VEGETATION ; KNOWLEDGE ; SELECTION ; VALLEY ; STOCKS ; COVER ; MODEL |
WOS类目 | Geography, Physical ; Geosciences, Multidisciplinary |
WOS研究方向 | Physical Geography ; Geology |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/199269 |
作者单位 | 1.Isfahan Univ Technol, Dept Soil Sci, Coll Agr, Esfahan 8415683111, Iran; 2.Shahid Bahonar Univ Kerman, Dept Soil Sci, Coll Agr, Kerman, Iran; 3.Univ Ghent, Dept Soil Management, Coupure Links 653, B-9000 Ghent, Belgium |
推荐引用方式 GB/T 7714 | Zeraatpisheh, Mojtaba,Ayoubi, Shamsollah,Jafari, Azam,et al. Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran[J],2017,285:186-204. |
APA | Zeraatpisheh, Mojtaba,Ayoubi, Shamsollah,Jafari, Azam,&Finke, Peter.(2017).Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran.GEOMORPHOLOGY,285,186-204. |
MLA | Zeraatpisheh, Mojtaba,et al."Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran".GEOMORPHOLOGY 285(2017):186-204. |
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