Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1007/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
![]() |
ISSN | 0167-6369 |
EISSN | 1573-2959 |
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 |
推荐引用方式 GB/T 7714 | 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). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。