Open Access
Origin and spatial distribution of heavy metals in a soil map unit of Sri Lanka.
U. K. P. S. Sanjeevani,S. P. Indraratne,W. A. U. Vitharana,Rohan Weerasooriya,F. Rosemary +4 more
- 01 Jan 2013
- pp 197-199
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About: The article was published on 01 Jan 2013. and is currently open access. The article focuses on the topics: Soil map.
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Citations
Spatial distribution of smelter emission heavy metals on farmland soil
TL;DR: The results of this work indicate that the soil in the study area was polluted by Cd and Pb emissions from more than one polluting sources, and the variation of Cd, Pb concentration and Cd/Cd ratios of samples to the distance of the pollution source can be potentially used for pollution source identification.
Trend analysis of global usage of digital soil mapping models in the prediction of potentially toxic elements in soil/sediments: a bibliometric review.
Prince Chapman Agyeman,Samuel Kudjo Ahado,Luboš Borůvka,James Kobina Mensah Biney,Vincent Yaw Oppong Sarkodie,Ndiye M. Kebonye,John Kingsley +6 more
TL;DR: A review of articles, summarize and analyse the spatial prediction of potentially toxic elements, determine and compare the models' usage as well as their performance over time, and reveals the complementary role machine learning algorithms and the geostatistical models play in DSM.
29
References
Spatial distribution of smelter emission heavy metals on farmland soil
TL;DR: The results of this work indicate that the soil in the study area was polluted by Cd and Pb emissions from more than one polluting sources, and the variation of Cd, Pb concentration and Cd/Cd ratios of samples to the distance of the pollution source can be potentially used for pollution source identification.
Trend analysis of global usage of digital soil mapping models in the prediction of potentially toxic elements in soil/sediments: a bibliometric review.
Prince Chapman Agyeman,Samuel Kudjo Ahado,Luboš Borůvka,James Kobina Mensah Biney,Vincent Yaw Oppong Sarkodie,Ndiye M. Kebonye,John Kingsley +6 more
TL;DR: A review of articles, summarize and analyse the spatial prediction of potentially toxic elements, determine and compare the models' usage as well as their performance over time, and reveals the complementary role machine learning algorithms and the geostatistical models play in DSM.
29