Arid
DOI10.1007/s10661-019-7844-y
Dataset characteristics influence the performance of different interpolation methods for soil salinity spatial mapping
Sangani, Mahmood Fazeli1; Khojasteh, Davood Namdar2; Owens, Gary3
通讯作者Sangani, Mahmood Fazeli
来源期刊ENVIRONMENTAL MONITORING AND ASSESSMENT
ISSN0167-6369
EISSN1573-2959
出版年2019
卷号191期号:11
英文摘要This study compared the performance of different interpolation methods for mapping soil salinity of three different agricultural fields having the same land use but different dataset characteristics. Four common spatial interpolation methods including global polynomial interpolation (GPI), inverse distance weighted (IDW), ordinary kriging (OK), and radial basis functions (RBF) were employed for mapping soil EC. The performance of interpolation methods in predicting soil EC was evaluated based on mean bias error, root mean square error, mean absolute percentage error, and coefficient of determinations criteria. Results showed that dataset characteristics, including central tendency and distribution, were significantly different among the studied fields. Experimental semivariogram and fitted model parameters indicated that three studied fields were also different in their spatial dependence strength. Considering all of the performance assessment measures used, the best interpolation method for fields A and C was OK and IDW for field B. The performance of interpolation methods was found to be affected by data characteristics of the studied fields, which were mostly ascribed to management practices. This study suggests in order to obtain accurate mapping of soil salinity in agricultural fields, it is essential to first find the best spatial interpolation method compatible with the characteristics of the collected data from the selected agricultural land.
英文关键词Deterministic method Geostatistics Interpolation Northern plains of Varamin city
类型Article
语种英语
国家Iran ; Australia
收录类别SCI-E
WOS记录号WOS:000499199400003
WOS关键词OASIS
WOS类目Environmental Sciences
WOS研究方向Environmental Sciences & Ecology
EI主题词2019-11-01
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/310553
作者单位1.Univ Guilan, Fac Agr Sci, Dept Soil Sci, Rasht, Iran;
2.Shahed Univ, Fac Agr Sci, Dept Soil Sci, POB 18151-159, Tehran, Iran;
3.Univ South Australia, Future Ind Inst, Mawson Lakes, SA 5095, Australia
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Sangani, Mahmood Fazeli,Khojasteh, Davood Namdar,Owens, Gary. Dataset characteristics influence the performance of different interpolation methods for soil salinity spatial mapping[J],2019,191(11).
APA Sangani, Mahmood Fazeli,Khojasteh, Davood Namdar,&Owens, Gary.(2019).Dataset characteristics influence the performance of different interpolation methods for soil salinity spatial mapping.ENVIRONMENTAL MONITORING AND ASSESSMENT,191(11).
MLA Sangani, Mahmood Fazeli,et al."Dataset characteristics influence the performance of different interpolation methods for soil salinity spatial mapping".ENVIRONMENTAL MONITORING AND ASSESSMENT 191.11(2019).
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