New mangrove forest tree age assessment method based on dense time remote sensing data
A technology for remote sensing data and mangroves, applied in the field of satellite remote sensing image processing, can solve the problems of high-frequency random changes, large differences in change information, and limited application, and achieve the effect of strong applicability and accurate acquisition.
Active Publication Date: 2021-05-07
CHINA ACADEMY OF SPACE TECHNOLOGY
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However, at present, the application of this method in the age estimation of young mangroves is very limited. This is mainly because the spectrum of young mangroves is affected by the tide, and there will be high-frequency and random changes, which do not meet the forest spectrum time set by common change detection algorithms. Change characteristics, if these algorithms are applied to the change detection of new mangroves, the change information obtained is quite different from the actual
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[0044] In order to better understand the above technical solutions, the technical solutions of the present application will be described in detail below through the accompanying drawings and specific examples. It should be understood that the embodiments of the present application and the specific features in the examples are detailed descriptions of the technical solutions of the present application, and It is not a limitation to the technical solutions of the present application, and the embodiments of the present application and the technical features in the embodiments can be combined without conflict.
[0045] A kind of new-born mangrove tree age assessment method based on intensive time remote sensing data provided by the embodiment of the present application will be described in further detail below in conjunction with the accompanying drawings, and specific implementation methods may include (such as Figure 1~3 shown):
[0046] Step 1: Obtain all the US Landsat surfac...
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The invention discloses a new mangrove forest age evaluation method based on dense time remote sensing data, and belongs to the technical field of satellite remote sensing image processing. The invention provides a new mangrove forest tree age assessment method based on dense time remote sensing data, and solves the problems in the existing tree age assessment method based on dense time sequence remote sensing data change detection, forest spectrum time change characteristics (for example, according with sine or cosine distribution) set by a detection algorithm do not conform to the law that a new mangrove forest spectrum generates high-frequency and random change under the influence of tides and cannot be used for new mangrove forest age evaluation, and the like, and the target of rapidly and accurately obtaining large-range new mangrove forest age results is achieved. The method is high in applicability, not only can be used for monitoring and managing the mangrove forest, but also contributes to revealing the carbon income and expenditure process of the mangrove forest and evaluating the biodiversity of the mangrove forest area.
Description
technical field [0001] The invention relates to a new mangrove tree age assessment method based on intensive time remote sensing data, and belongs to the technical field of satellite remote sensing image processing. Background technique [0002] Accurate estimation of the age of young mangroves (mainly referring to mangroves less than 30 years old) is the key to quantitatively assessing the carbon budget of mangroves. The study found that biochemical processes such as photosynthesis and respiration in young mangroves changed significantly with tree age, while the processes in mature mangroves basically tended to be stable. In addition, the parameter sensitivity analysis results of the biochemical process-based mangrove emission assessment model (MCAT-DNDC) also showed that the age of young mangroves had a greater impact on the carbon emission assessment results. [0003] The traditional tree age determination mainly adopts the combination of field investigation and indoor e...
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IPC IPC(8): G06F17/18
CPCG06F17/18
Inventor 胡洛佳李纹宇于志同陈鹭真张韵
Owner CHINA ACADEMY OF SPACE TECHNOLOGY