A biomass model research and construction method based on a hyperspectral remote sensing and photogrammetry technology
A hyperspectral remote sensing and photogrammetry technology, applied in the field of biomass model research and construction, can solve problems such as the lack of a systematic biomass estimation process and calculation method, and achieve the goals of reducing field workload, improving measurement efficiency, and efficient calculation Effect
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2019-03-05
- Estimated Expiration
- Not applicable · inactive patent
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Abstract
Description
1. Technical field
[0001] The invention relates to a method for developing and building a biomass model, in particular to a method for developing and building a vegetation biomass model based on hyperspectral remote sensing technology, unmanned aerial vehicle photogrammetry technology and ground photogrammetry technology. 2. Technical background
[0002] As the main body of terrestrial ecosystems, vegetation plays a huge role in maintaining carbon balance and maintaining species diversity, and also has an important impact on surrounding microclimate changes. Its huge advantages in improving the environment have attracted widespread attention. As the largest terrestrial vegetation community, the forest community has a strong carbon sink capacity of its ecosystem, which has become a research topic of major scientific research programs such as the International Geosphere-Biosphere Program, the International Human Factors Program of Global Environmental Change, the World Climate ...
Examples
Embodiment Construction
[0033] Below in conjunction with specific embodiment, the present invention will be further described, specifically:
[0034] Using hyperspectral remote sensing technology to extract vegetation characteristic parameters, the steps to develop a biomass model are as follows:
[0035] (1) Spectral data preprocessing, select the average value of the measured values in a certain range before and after a measuring point on the spectral curve, as the value of this point, give the sequence of N measuring points {R i , i=1, 2, 3...N}, wherein, the value of point i includes the average value of each K point before and after, using the mathematical model (1) Among them, the new value of point i is R′ i , replaced by the average value of 2k+1 points including this point, and then determine the value of this point on the spectral curve;
[0036] (2) Hyperspectral data feature parameter extraction, using mathematical model (2) FDR λ(r) =(R λ(j+1) -R λ(j) ) / Δλ to process hyperspectra...