A screening method for optimal environmental variables for spatiotemporal dynamic prediction of soil organic carbon pool

Abstract

The invention relates to an optimal environment variable screening method for time-space dynamic prediction of a soil organic carbon pool. Soil databases in different periods, and dynamic and static environment variable sets are collected and sorted; and according to the timeliness of soil data, an effective time period, namely, "a time slice" for simulating the soil carbon pool is stipulated. Various attribute information of various dynamic and static environment variables is analyzed according to soil organic carbon density information in different landscape areas, so that an analytic hierarchy process and expert knowledge are used for constructing an effective optimal environment variable set in the specific time slice.

Description

technical field [0001] The invention relates to a soil organic carbon pool spatiotemporal dynamic prediction optimal environmental variable screening method, which belongs to the technical field of soil measurement. Background technique [0002] Soil organic carbon is a collective term for the humus produced by animal and plant residues, microorganisms, and soil microorganisms. Compared with soil inorganic carbon pools, soil organic carbon content is more sensitive to soil tillage and land use changes. The problem of global warming since the industrial revolution has forced governments to pay more and more attention to the reduction of greenhouse gas emissions. According to relevant statistics, the organic carbon storage within one meter of soil is the most important component of the soil carbon pool. As the largest carbon pool in the global terrestrial ecosystem, the soil carbon pool is about the sum of the atmospheric carbon pool and the terrestrial ecosystem carbon pool...

AI Technical Summary

Problems solved by technology

[0007] (2) Existing spatial prediction technology pays more attention to model construction and uncertainty assessment, and relatively ignores the selection of model input parameters

These environmental variables have a certain degree of uncertainty and interact with each other, and it is difficult to accurately define them with the traditional variable screening mechanism.

[0009] To sum up, the above-mentioned technical defects have seriously affected the spatial-temporal dynamic estimation of soil carbon pools in different sectors, which not only reduces the efficiency and accuracy of the application sector in the production and processing of soil information products, but also brings great challenges to national economic planning and regulation. potential loss

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