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Prediction of heavy metal spatial distribution in soils of typical industrial zones utilizing 3D convolutional neural networksChao Liu 1 , Lan Chen 1 , Guoqing Ni 2 , Xiuhe Yuan 1 , Shuai He 3 & Sheng Miao 2?Land resources are vital for urban development and construction. Abandoned industrial areas often contain large amounts of heavy metals from past industrial activities. Accurate knowledge of soil pollutant content and spatial distribution is crucial to avoid health risks and achieve sustainable soil use. However, due to the limitation of human, material and fi nancial resources, it is dif f i cult to carry out intensive detection of soil heavy metals in polluted areas. This problem can be solved by using known soil heavy metal content data to predict the heavy metals in unknown regions. This study utilizes a three-dimensional Convolutional Neural Network (3DCNN) model, combined with spatial location and soil physicochemical properties, to predict heavy metal in a typical industrial zone in Qingdao City. The results show that the R 2 of 3DCNN for predicting cadmium (Cd), lead (Pb), copper (Cu) and nickel (Ni) are 0.59, 0.59, 0.77 and 0.51, respectively. Therefore, 3DCNN can be used as an ef f ective method for spatial prediction of soil heavy metals, which can reduce the cost of sampling and laboratory analysis. The three-dimensional spatial distribution analysis revealed that Cd and Pb were concentrated in the surface soil layer and gradually decreased with the depth, while Cu and Ni contents are mainly concentrated in the range of 3 m, exhibiting downward migration. Therefore, heavy metal enrichment has occurred in this area, and soil heavy metal treatment should be carried out before redevelopment.Keywords Industrial area soil, Soil contamination, Heavy metals, Content prediction, 3DCNN, Spatial distribution characteristicsAbbreviations3DCNN Th ree-dimensional convolutional neural networkCd CadmiumCEC Cation exchange capacityCu CopperCV Coef f i cient of variationMAE Mean absolute errorMSE Mean squared errorNi NickelOK Ordinary KrigingPb LeadR 2 Coef f i cient of determinationRF Random ForestRMSE Root mean squared errorSoil is an important component of the terrestrial ecosystem and the material basis on which human survival depends, but it is also the ultimate carrier of heavy metals 1,2 . Urban soil quality is essential for the health of urban residents and ecosystems 3,4 . Heavy metal is one of the common pollutants in the environment, which has high 1 School of Environment and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China. 2 School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China. 3 Qingdao Borui Zhiyuan Vibration Anti-vibration Technology Co., Ltd, Qingdao 266000, China. ? email: smiao@qut.edu.cnOPENScientif i c Reports | (2025) 15:396 1 | https://doi.org/10.1038/s41598-024-84545-3www.nature.com/scientificreports