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    The distribution of soil pollutants is receiving increasing attention. The accurate determination of the soil pollution distribution in an area is becoming more important. To date, many soil quality surveys have already been carried out in China, and the use of these surveys to reflect soil pollution is worth examining. This article provides an example of the application of combined two-phase data to assess soil contamination in a region. Based on data acquired during two soil sampling phases in 2005 and 2015, we chose a typical watershed in southeast China as the study area. We analysed the data using spatial interpolation analysis, compared the results, and extracted points to perform point combination based on site conditions. Ultimately, these analyses allowed us to develop a new method involving the use of multi-period data to evaluate the soil quality on a regional scale. In the ten years from 2005 to 2015, apparent changes in soil pollution occurred. We found that the area with no change in soil pollution accounts for 46.98% of the total basin and the area demonstrating a soil pollution increase accounts for 47.25% of the total basin, while the area exhibiting a soil pollution reduction only accounts for 5.78% of the whole area. The average accuracy of the combined points increased to 89% from 76 and 81%. The analysis of the land-use types and spatial locations during the two periods revealed no direct relationship between the soil contamination changes and the changes in the total number of land-use types, but a correlation was observed with the intensity of human activities at the spatial locations. This paper proposes a new method for the spatial assessment of soil pollution based using multiple periods of existing data on the above analysis. © 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

    Citation

    Zedong Yang, Zhongke Bai, Zhiheng Qin. A new soil sampling design method using multi-temporal and spatial data fusion. Environmental science and pollution research international. 2022 Mar;29(14):21023-21033

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    PMID: 34748180

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