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Spatial Estimation of Soil Organic Matter in Karst Peak-cluster Depression

Auteur(s):




Médium: article de revue
Langue(s): en 
Publié dans: The Open Civil Engineering Journal, , n. 1, v. 9
Page(s): 1022-1027
DOI: 10.2174/1874149501509011022
Abstrait:

In order to enhance the accuracy of spatial estimation of soil organic matter (SOM), spatial predictions of SOM in 0~20 cm depth were conducted in Guohua Ecological Experimental Area of Minister of Land and Resource of the People's Republic of China. Analysis of multiple linear stepwise regressions showed that the two terrain attributes of relief degree of land surface (RS) and distance from ridge of mountains (DFR) entered into the regression equation. Therefore, RS and DFR were selected as auxiliary variables to predict SOM by MCOK and RK methods. The accuracy of spatial estimation of SOM was compared among methods of ordinary kriging (OK), multivariable cokriging (MCOK) and regression kriging (RK). Results showed that RK and MCOK methods with terrain attributes as auxiliary variables could enhance the accuracy of spatial estimation of SOM, and MCOK method could promote the accuracy notable by 31.33%. This study can provide a new idea and method for evaluation of soil quality in karst areas.

Copyright: © 2016 Li Hui et al.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10175461
  • Publié(e) le:
    30.12.2018
  • Modifié(e) le:
    02.06.2021