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Spatial Prediction of Soil Organic Matter Using Geostatistics and Topographic Unit Zoning Integrated in GIS: A Case Study

Received: May 30, 2019    Accepted: Oct. 22, 2019    Published: Oct. 28, 2019
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Abstract

The spatial distribution of soil organic matter (SOM) has a close connection with topography. To understand the effects of topographic synergy effects in traditional geostatistic methods, the influence of topography is considered in SOM geostatistic studies by combining geographic unit zoning and spatial prediction. We explored the changes in the SOM distribution between that obtained using spatial interpolation integrated with 13 different classical topographic units and determined using global interpolation with 6485 random soil samples obtained from Zhongxiang City, Hubei Province, China. The steps are as follows. At first, the terrain factors were calculated from the digital elevation data (DEM) and the topographic units were precisely divided into 13 different classical types more subtly by integrating the terrain factors. The regions were divided, which was based on terrain classification rules formed by the distribution of terrain factors in different landforms. Secondly, soil samples were collected in different topographic types, and the distribution of SOM for each sample set in different topographic units was generated by ordinary Kriging. Then, the corresponding results of interpolation for each sample set were segmented based on topographic unit region, and combining the result in each region, the spatial distribution of SOM based on topographic unit was obtained. Finally, verification and comparison with the accuracy of each SOM distributions were performed, which were obtained by using topography based geostatistics and traditional global geostatistics, respectively. Our results indicated that more accurate SOM spatial distributions can be obtained using the proposed method, especially in regions with gentle topography, such as ridge, shoulder, summit, toe slope (north/northeast side), and low-lying terrain units.

DOI 10.11648/j.earth.20190805.15
Published in Earth Sciences ( Volume 8, Issue 5, October 2019 )
Page(s) 294-302
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Soil Organic Matter, Geostatistics, Topographic Unit, Spatial Prediction

References
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  • APA Style

    Zhou Ziyan, Fu Peihong, Han Zongwei, Huang Wei. (2019). Spatial Prediction of Soil Organic Matter Using Geostatistics and Topographic Unit Zoning Integrated in GIS: A Case Study. Earth Sciences, 8(5), 294-302. https://doi.org/10.11648/j.earth.20190805.15

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    ACS Style

    Zhou Ziyan; Fu Peihong; Han Zongwei; Huang Wei. Spatial Prediction of Soil Organic Matter Using Geostatistics and Topographic Unit Zoning Integrated in GIS: A Case Study. Earth Sci. 2019, 8(5), 294-302. doi: 10.11648/j.earth.20190805.15

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    AMA Style

    Zhou Ziyan, Fu Peihong, Han Zongwei, Huang Wei. Spatial Prediction of Soil Organic Matter Using Geostatistics and Topographic Unit Zoning Integrated in GIS: A Case Study. Earth Sci. 2019;8(5):294-302. doi: 10.11648/j.earth.20190805.15

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  • @article{10.11648/j.earth.20190805.15,
      author = {Zhou Ziyan and Fu Peihong and Han Zongwei and Huang Wei},
      title = {Spatial Prediction of Soil Organic Matter Using Geostatistics and Topographic Unit Zoning Integrated in GIS: A Case Study},
      journal = {Earth Sciences},
      volume = {8},
      number = {5},
      pages = {294-302},
      doi = {10.11648/j.earth.20190805.15},
      url = {https://doi.org/10.11648/j.earth.20190805.15},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.earth.20190805.15},
      abstract = {The spatial distribution of soil organic matter (SOM) has a close connection with topography. To understand the effects of topographic synergy effects in traditional geostatistic methods, the influence of topography is considered in SOM geostatistic studies by combining geographic unit zoning and spatial prediction. We explored the changes in the SOM distribution between that obtained using spatial interpolation integrated with 13 different classical topographic units and determined using global interpolation with 6485 random soil samples obtained from Zhongxiang City, Hubei Province, China. The steps are as follows. At first, the terrain factors were calculated from the digital elevation data (DEM) and the topographic units were precisely divided into 13 different classical types more subtly by integrating the terrain factors. The regions were divided, which was based on terrain classification rules formed by the distribution of terrain factors in different landforms. Secondly, soil samples were collected in different topographic types, and the distribution of SOM for each sample set in different topographic units was generated by ordinary Kriging. Then, the corresponding results of interpolation for each sample set were segmented based on topographic unit region, and combining the result in each region, the spatial distribution of SOM based on topographic unit was obtained. Finally, verification and comparison with the accuracy of each SOM distributions were performed, which were obtained by using topography based geostatistics and traditional global geostatistics, respectively. Our results indicated that more accurate SOM spatial distributions can be obtained using the proposed method, especially in regions with gentle topography, such as ridge, shoulder, summit, toe slope (north/northeast side), and low-lying terrain units.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Spatial Prediction of Soil Organic Matter Using Geostatistics and Topographic Unit Zoning Integrated in GIS: A Case Study
    AU  - Zhou Ziyan
    AU  - Fu Peihong
    AU  - Han Zongwei
    AU  - Huang Wei
    Y1  - 2019/10/28
    PY  - 2019
    N1  - https://doi.org/10.11648/j.earth.20190805.15
    DO  - 10.11648/j.earth.20190805.15
    T2  - Earth Sciences
    JF  - Earth Sciences
    JO  - Earth Sciences
    SP  - 294
    EP  - 302
    PB  - Science Publishing Group
    SN  - 2328-5982
    UR  - https://doi.org/10.11648/j.earth.20190805.15
    AB  - The spatial distribution of soil organic matter (SOM) has a close connection with topography. To understand the effects of topographic synergy effects in traditional geostatistic methods, the influence of topography is considered in SOM geostatistic studies by combining geographic unit zoning and spatial prediction. We explored the changes in the SOM distribution between that obtained using spatial interpolation integrated with 13 different classical topographic units and determined using global interpolation with 6485 random soil samples obtained from Zhongxiang City, Hubei Province, China. The steps are as follows. At first, the terrain factors were calculated from the digital elevation data (DEM) and the topographic units were precisely divided into 13 different classical types more subtly by integrating the terrain factors. The regions were divided, which was based on terrain classification rules formed by the distribution of terrain factors in different landforms. Secondly, soil samples were collected in different topographic types, and the distribution of SOM for each sample set in different topographic units was generated by ordinary Kriging. Then, the corresponding results of interpolation for each sample set were segmented based on topographic unit region, and combining the result in each region, the spatial distribution of SOM based on topographic unit was obtained. Finally, verification and comparison with the accuracy of each SOM distributions were performed, which were obtained by using topography based geostatistics and traditional global geostatistics, respectively. Our results indicated that more accurate SOM spatial distributions can be obtained using the proposed method, especially in regions with gentle topography, such as ridge, shoulder, summit, toe slope (north/northeast side), and low-lying terrain units.
    VL  - 8
    IS  - 5
    ER  - 

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Author Information
  • College of Resource and Environment, Huazhong Agricultural University, Wuhan, China

  • College of Resource and Environment, Huazhong Agricultural University, Wuhan, China

  • Department of Tourism and Geography, Tongren University, Tongren, Guizhou, China

  • College of Resource and Environment, Huazhong Agricultural University, Wuhan, China

  • Section