一种植被净初级生产力估算方法、装置及设备、存储介质
By integrating multi-scale data and identifying stress factors, the problems of data accuracy and gaps in large-scale vegetation net primary productivity estimation were solved, achieving efficient and accurate vegetation net primary productivity estimation applicable to complex ecosystems.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING NORMAL UNIV AT ZHUHAI
- Filing Date
- 2026-03-12
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies face problems such as insufficient data accuracy, data gaps, and low computational efficiency in large-scale vegetation net primary productivity estimation. In particular, they are difficult to meet the needs of refined research when the high-resolution data classification system is coarse or the spatial resolution is low.
By acquiring land cover data, land use classification data, surface reflectance data, and meteorological and climatic data, multi-scale fusion and quality control are performed to identify temperature stress factors and water stress factors. Combined with the photosynthetically active radiation absorption ratio, high-precision estimation of vegetation net primary productivity is achieved.
It improves the efficiency and accuracy of vegetation net primary productivity estimation, reduces data gaps, significantly enhances the parameterization accuracy of complex ecosystems such as forests, and is suitable for integrity estimation in cloudy and rainy areas.
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Figure CN121808298B_ABST
Abstract
Citation Information
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