Land system change causal structure recognition method, system and device

Abstract

The invention discloses a land system change causal structure recognition method, system and device. The method comprises the following steps: land use type change data and influencing factor data ina plurality of time periods in a study area are acquired; with the land use type change data and the influencing factor data as model variables, a causal structure network is constructed; and a causalrelationship between the model variables in the causal structure network is recognized based on a PC algorithm, and a causal graph model is obtained. The relationship between the land use type changes and the influencing factors in the study area is considered comprehensively, the PC algorithm is used to recognize the causal relationship between the model variables in the causal structure network, and the causal structure among the land system variables can be effectively recognized; the method can integrate changes of each land use type in the land system and each factor influencing the landsystem changes between different systems and the complexity characteristic of the land system is better met; and the method can be widely applied to the field of environmental modeling.

Description

technical field [0001] The invention relates to the field of environmental modeling, in particular to a method, system and device for identifying the causal structure of land system changes. Background technique [0002] Land is the carrier of human survival and an important natural resource that supports human production and life. The land system involves multiple factors such as society, economy, and ecological environment, and is closely related to multiple global focal issues such as population, resources, food security, and the environment. At a time when global change is facing severe challenges, through in-depth and detailed research on the causal structure and interaction of man-land coupling systems, the development of land system theory and applications will be promoted to provide in-depth thinking for global change research. [0003] The land system is a dynamic system formed by the interaction between man and land, so in essence, changes in the land system basic...

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Problems solved by technology

[0005] The limitations of these statistical models are: (1) correlation analysis cannot identify causality, and these statistical models based on correlation analysis cannot identify the causal structure of land system changes; (2) these models assume that the independent variables of the model are independent of each other and have no interaction, Therefore their responses to the dependent variable are also independent

However, in real land systems, different land uses and driving factors often interact and influence each other, and these assumptions violate the complexity of real land systems

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