A spatial sampling network design method for soil organic carbon considering the non-stationary characteristics of spatio-temporal distribution

Abstract

The invention relates to a soil organic carbon spatial sampling network design method giving consideration to the non-stationary characteristic of spatial-temporal distribution. The soil organic carbon spatial sampling network design method comprises: firstly, extracting basic data of soil organic carbon spatial sampling network design and carrying out integration; then establishing a regression relationship between soil organic carbon spatial-temporal changes and multiple time series attributes by applying a spatial-temporal regression method, and mapping a soil organic carbon spatial-temporal changing process into a spatial-temporal stochastic process formed by a soil organic carbon multi-factor spatial-temporal regression tendency and a regression residual; finally, constructing a soil organic carbon spatial sampling network design model, using the data as model input data, evaluating a fitness function, establishing a mapping relationship between a sampling scheme design problem and a particle swarm optimization algorithm, and solving to obtain a soil organic carbon spatial sampling network optimization scheme. According to the method, investigation accuracy is greatly improved, meanwhile, rapid convergence and extra-strong optimizing capacity of the particle swarm optimization algorithm are sufficiently played, and reasonability, applicability and design efficiency of a soil organic carbon spatial sampling network are promoted.

Description

technical field [0001] The invention relates to the field of land resources investigation, in particular to a soil organic carbon spatial sampling network design method. Background technique [0002] Soil organic carbon pool is the largest active carbon pool in terrestrial ecosystems, and plays a key role in slowing down carbon release and regulating global carbon balance. Accurate determination of soil organic carbon storage has become the focus of the current scientific community and governments. In my country, with the goal of "practicing energy conservation and low carbon, and building a beautiful China", the timely implementation of high-precision soil organic carbon sampling surveys and monitoring will provide strong decision-making support for the scientific formulation of low-carbon development strategies. Facing the multi-level needs of scientific research and development, it is imperative to study efficient soil organic carbon sampling methods in time and space. ...

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Problems solved by technology

The specific performance is as follows: (1) Complete repeated sampling and complete replacement sampling can only describe the spatial non-stationarity of variables, ignoring its time-varying characteristics; (2) Adaptive sampling methods involve the use of hierarchical methods or geometric ratio methods to describe space-time Non-stationary and spatial-temporal anisotropy, but it is still unable to accurately describe the continuous non-stationary characteristics of space-time

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