{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T15:22:43Z","timestamp":1784733763695,"version":"3.55.0"},"reference-count":104,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2020,11,17]],"date-time":"2020-11-17T00:00:00Z","timestamp":1605571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["201706320317"],"award-info":[{"award-number":["201706320317"]}],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Soil pollution by potentially toxic elements (PTEs) has become a core issue around the world. Knowledge of the spatial distribution of PTEs in soil is crucial for soil remediation. Portable X-ray fluorescence spectroscopy (p-XRF) provides a cost-saving alternative to the traditional laboratory analysis of soil PTEs. In this study, we collected 293 soil samples from Fuyang County in Southeast China. Subsequently, we used several geostatistical methods, such as inverse distance weighting (IDW), ordinary kriging (OK), and empirical Bayesian kriging (EBK), to estimate the spatial variability of soil PTEs measured by the laboratory and p-XRF methods. The final maps of soil PTEs were outputted by the model averaging method, which combines multiple maps previously created by IDW, OK, and EBK, using both lab and p-XRF data. The study results revealed that the mean PTE content measured by the laboratory methods was as follows: Zn (127.43 mg kg\u22121) &gt; Cu (31.34 mg kg\u22121) &gt; Ni (20.79 mg kg\u22121) &gt; As (10.65 mg kg\u22121) &gt; Cd (0.33 mg kg\u22121). p-XRF measurements showed a spatial prediction accuracy of soil PTEs similar to that of laboratory analysis measurements. The spatial prediction accuracy of different PTEs outputted by the model averaging method was as follows: Zn (R2 = 0.71) &gt; Cd (R2 = 0.68) &gt; Ni (R2 = 0.67) &gt; Cu (R2 = 0.62) &gt; As (R2 = 0.50). The prediction accuracy of the model averaging method for five PTEs studied herein was improved compared with that of the laboratory and p-XRF methods, which utilized individual geostatistical methods (e.g., IDW, OK, EBK). Our results proved that p-XRF was a reliable alternative to the traditional laboratory analysis methods for mapping soil PTEs. The model averaging approach improved the prediction accuracy of the soil PTE spatial distribution and reduced the time and cost of monitoring and mapping PTE soil contamination.<\/jats:p>","DOI":"10.3390\/rs12223775","type":"journal-article","created":{"date-parts":[[2020,11,17]],"date-time":"2020-11-17T22:46:46Z","timestamp":1605653206000},"page":"3775","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Improved Mapping of Potentially Toxic Elements in Soil via Integration of Multiple Data Sources and Various Geostatistical Methods"],"prefix":"10.3390","volume":"12","author":[{"given":"Fang","family":"Xia","sequence":"first","affiliation":[{"name":"College of Economics and Management, Zhejiang A&amp;F University, Hangzhou 311300, China"},{"name":"Zhejiang Province Key Cultivating Think Tank\u2014Research Academy for Rural Revtitalization of Zhejiang Province, Zhejiang A&amp;F University, Hangzhou 311300, China"},{"name":"Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9353-0307","authenticated-orcid":false,"given":"Bifeng","family":"Hu","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"},{"name":"Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"},{"name":"Sciences de la Terre et de l\u2019Univers, Orl\u00e9ans University, 45067 Orl\u00e9ans, France"},{"name":"Unit\u00e9 de Recherche en Science du Sol, INRA, 45075 Orl\u00e9ans, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youwei","family":"Zhu","sequence":"additional","affiliation":[{"name":"Protection and Monitoring Station of Agricultural Environment, Bureau of Agriculture, Hangzhou 310020, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjun","family":"Ji","sequence":"additional","affiliation":[{"name":"College of land Science and Technology, China Agricultural University, Beijing 100085, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3914-5402","authenticated-orcid":false,"given":"Songchao","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"},{"name":"Unit\u00e9 InfoSol, INRAE, 45075 Orl\u00e9ans, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongyun","family":"Xu","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"},{"name":"Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhou","family":"Shi","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"},{"name":"Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/j.geoderma.2011.11.014","article-title":"Mapping soil Pb stocks and availability in mainland France combining regression trees with robust geostatistics","volume":"170","author":"Lacarce","year":"2012","journal-title":"Geoderma"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Hu, B.F., Xue, J., Zhou, Y., Shao, S., Fu, Z., Li, Y., Chen, S.C., Qi, L., and Shi, Z. 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