A method for evaluating the effect of the livelihood transition of farmers and herders based on multi-scale data fusion
By using multi-scale data fusion and multi-objective programming models, the cross-scale correlation between farmers' livelihood decisions and ecosystem service functions was solved, realizing the sustainability of farmers' livelihood transformation programs and the coordination of ecological economy, and improving the systematicness and dynamism of the assessment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING NORMAL UNIVERSITY
- Filing Date
- 2025-10-15
- Publication Date
- 2026-07-07
AI Technical Summary
Existing technologies are insufficient to reveal the cross-scale natural connections and dynamic feedback mechanisms through which farmers' and herders' micro-livelihood decisions are transmitted to the evolution of ecosystem service functions via land use change. The assessment results are fragmented and lack systematicity, failing to achieve the connection and linkage between natural and socio-economic factors in a multi-level system, and unable to respond to the dynamic scenario evolution of changes in ecological value.
By fusing multi-scale data, including livelihood activities and assets at the farmer and herder scale and land use data at the landscape scale, we use income-asset regression models and latent variable clustering analysis to generate livelihood strategy classification results. We combine multiple Logit regression models to analyze driving factors, construct agent-based models to simulate land use decisions, use the equivalent factor method to assess changes in ecosystem service value, and construct multi-objective programming models to generate sustainable livelihood transformation solutions.
It has enabled the quantification and simulation of the cross-scale dynamic feedback mechanism between farmers' and herders' livelihood decisions and ecosystem service functions, generated sustainable livelihood transformation solutions, improved the rationality of land use change simulation and the dynamic assessment of ecosystem service value, and achieved synergistic optimization of ecological and economic goals.
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