Soil organic carbon content prediction method based on random forest-ordinary Kriging method

A common kriging and random forest technology, applied in the field of soil organic carbon content prediction, can solve the problems of ignoring the spatial autocorrelation of variables and affecting the prediction accuracy of soil organic carbon.

Inactive Publication Date: 2019-02-15
FUJIAN AGRI & FORESTRY UNIV
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Problems solved by technology

However, like other machine learning models, the random forest model only considers the relationship between soil organic carbon content and environmental factors, ignoring the spatial autocorrelation of variables, which in turn affects the prediction accuracy of soil organic carbon

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Embodiment

[0044] In this embodiment, a specific research area is selected for illustration. Overview of the study area: The study area is located in Hetian Town, Changting County, Fujian Province, in the southern section of the Wuyi Mountains (25°33′N~25°48′N, 116°18′E~116°31′E), with a total area of 296km2, including 213km2 of mountain area, the main dominant tree species are masson pine (Pinus massoniana) and Chinese fir (Cunninghamia lanceolata). This area has a mid-subtropical monsoon climate, with an average annual temperature of 17.5°C to 18.8°C and an average annual rainfall of 1700mm. The topography is dominated by low mountains and hills, and the soil type is dominated by red soil. It is a typical red soil hilly area in the south. Due to historical reasons, the mountainous natural vegetation in the study area has been severely damaged, and soil erosion has been severe, making it one of the areas with the most serious water and soil erosion in southern red soil. In recent years...

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Abstract

The invention relates to a soil organic carbon content prediction method based on a random forest-ordinary Kriging method. The method comprises the following steps: firstly, determining organic carbons in a soil sample; secondly, extracting environmental factors and screening the environmental factors related to the soil organic carbon content; finally, predicting the spatial distribution of the soil organic carbon content based on a random forest-ordinary Kriging model and the related environmental factors. The method provided by the invention realizes the spatial prediction of the soil organic carbon content by means of a relationship between the soil organic carbons and the environmental factors (topography, climate and vegetation).

Description

technical field [0001] The invention relates to the application field of remote sensing technology, in particular to a method for predicting soil organic carbon content based on the random forest-ordinary Kriging method. Background technique [0002] Due to the spatio-temporal variability of regional soil properties, traditional sampling and mapping methods are difficult to accurately characterize the spatial distribution characteristics and continuity of SOC, and it is difficult to obtain high-precision SOC information. In recent years, with the rapid development of remote sensing information technology, digital soil mapping (DSM) has become an effective means to accurately obtain the distribution of soil organic carbon in regions with large spatial heterogeneity. At present, DSM is mainly based on the soil-landscape model, that is, to obtain environmental factors closely related to soil formation through "3S" technology and computer technology, and to use mathematical mode...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N33/24G06F17/18
CPCG01N33/24G06F17/18
Inventor 姚雄余坤勇刘健邓洋波赖壮杰
Owner FUJIAN AGRI & FORESTRY UNIV
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