Comparison of Methods of Prediction of Heavy Metals in the Soil Using R
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Springer International Publishing
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https://link.springer.com/content/pdf/10.1007/978-3-031-17697-5_50
Reference19 articles.
1. Liao, Y., Li, D., Zhang, N.: Comparison of interpolation models for estimating heavy metals in soils under various spatial characteristics and sampling methods. Trans. GIS 22(2), 409–434 (2018). https://doi.org/10.1111/tgis.12319
2. Ouabo, R.E., Sangodoyin, A.Y., Ogundiran, M.B.: Assessment of ordinary kriging and inverse distance weighting methods for modeling chromium and cadmium soil pollution in E-waste sites in Douala Cameroon. J. Health Pollut. 10(26), 1 (2020). https://doi.org/10.5696/2156-9614-10.26.200605
3. Xia, F., et al.: Improved mapping of potentially toxic elements in soil via integration of multiple data sources and various geostatistical methods. Remote Sens. 12(22), 1–26 (2020). https://doi.org/10.3390/rs12223775
4. Guagliardi, I., Cicchella, D., De Rosa, R.: A geostatistical approach to assess concentration and spatial distribution of heavy metals in urban soils. Water Air Soil Pollut. 223(9), 5983–5998 (2012). https://doi.org/10.1007/s11270-012-1333-z
5. Aval, M.Z., Miryousefiaval, Z., Zamani, A., Khosravi, Y.: Comparison of the interpolation of lead and zinc accumulation in the soils around zanjan lead and zinc corporation using laboratory and landsat data. J. Environ. Health Sci. Eng. 6(4), 153–161 (2020). https://doi.org/10.29252/jhehp.6.4.1
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