Dynamic evaluation and early warning method of vegetation index for monitoring ecological safety of river basin
By analyzing multi-temporal remote sensing images and ground data, a water-heat stress coupling index was constructed, which solved the problem of vegetation dynamic identification and early warning in watershed ecological security monitoring, realized personalized diagnosis and accurate early warning of the ecosystem, and improved the scientificity and timeliness of watershed ecological management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NORTHWEST INST OF ECO ENVIRONMENT & RESOURCES CAS
- Filing Date
- 2026-03-23
- Publication Date
- 2026-06-02
AI Technical Summary
Existing watershed ecological security monitoring technologies are unable to accurately identify the dynamic evolution of vegetation, cannot distinguish between natural seasonal fluctuations and abnormal ecological changes, ignore the time lag effect of environmental stress and vegetation response, and lack systematic quantification of the complex coupling effect of hydrothermal conditions. This leads to false alarms and missed alarms in the early warning system, and makes it impossible to accurately locate ecologically vulnerable transition zones and risk propagation paths.
By acquiring multi-temporal remote sensing image data and ground hydrological and meteorological observation data, multispectral vegetation index time series are extracted, seasonal baseline separation and fluctuation direction consistency analysis are performed, a hydrothermal stress coupling index is constructed, stress response delay coefficient and sensitivity coefficient are calculated, a dynamic assessment model of vegetation ecological security is established, ecological security level is generated and spatial gradient analysis is performed to achieve accurate early warning.
It breaks through the spatial and temporal limitations of ecological monitoring, enables early detection of ecological problems, achieves personalized diagnosis, accurately locates risk transmission nodes, improves the scientific and forward-looking nature of watershed ecological management, and provides technical support for regional sustainable development.
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