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An improved random forest-based remote sensing inversion method for the concentration of chlorophyll a in an offshore water body

A random forest and remote sensing inversion technology, applied to computer components, material analysis through optical means, measuring devices, etc., can solve problems such as unsatisfactory results

Inactive Publication Date: 2019-03-01
FUZHOU UNIV
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Problems solved by technology

Although the radiative transfer model has high precision and good versatility, it is based on the assumption that the absorption and scattering characteristics of each component of the water body are known, and a large amount of preliminary measurement and analysis work must be done on the corresponding water area. The measurement means and measurement data accuracy are limited, and the use effect is not ideal enough

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  • An improved random forest-based remote sensing inversion method for the concentration of chlorophyll a in an offshore water body
  • An improved random forest-based remote sensing inversion method for the concentration of chlorophyll a in an offshore water body
  • An improved random forest-based remote sensing inversion method for the concentration of chlorophyll a in an offshore water body

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Embodiment Construction

[0047] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0048] Please refer to figure 1 The present invention provides a method for remote sensing inversion of chlorophyll-a concentration in coastal waters based on improved random forest, comprising the following steps:

[0049] Step S1: Obtain the time series of original remote sensing images of the study area (the image acquisition time in this example is from May 2017 to May 2018), and perform geometric correction, area clipping, radiometric calibration, atmospheric correction and other presets on the remote sensing image data. Processing, to obtain the spectral reflectance of ground objects; sort out the obtained buoy data, and screen the measured abnormal values ​​according to the water quality information released by the Fujian Ocean Forecasting Station.

[0050] Specific steps are as follows:

[0051] Step S11: Collect the required time series image...

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Abstract

The invention relates to an offshore water chlorophyll a concentration remote sensing inversion method based on an improved random forest. remotely sensing image data by utilizing a time sequence; combining timing buoy observations, The method comprises the following steps of: establishing an intelligent remote sensing inversion model to carry out remote sensing inversion on the chlorophyll a concentration of an offshore water area by taking time continuous space sparse compensation as a modeling strategy and adopting an improved random forest-double-weight random forest method to obtain a very good inversion result, and visually and accurately displaying the spatial distribution of the chlorophyll a concentration of the offshore large range. The invention can provide a macroscopic, continuous and effective method for monitoring the concentration of chlorophyll a in the near-shore water body, can make up the deficiency of the traditional chlorophyll a concentration monitoring, and hashigher practical value.

Description

technical field [0001] The invention relates to the field of remote sensing information processing and application, in particular to a remote sensing inversion method for chlorophyll-a concentration in coastal waters based on improved random forest. Background technique [0002] Chlorophyll-a concentration is one of the important water quality parameters that can be directly retrieved by remote sensing, and it is often used to evaluate the eutrophication degree of coastal water bodies. The main means of traditional water quality monitoring are on-site sampling and laboratory analysis. This method has certain accuracy in precision and has local and typical representative significance. However, it can only obtain the surface water quality on the monitoring section and cannot reflect the entire water body. The overall temporal and spatial changes of the ecological environment are time-consuming, laborious, and costly, and real-time monitoring cannot be realized. Compared with ...

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Application Information

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IPC IPC(8): G06K9/62G01N21/17
CPCG01N21/17G01N2021/1797G06F18/211G06F18/214G06F18/24323
Inventor 苏华张明慧季博文
Owner FUZHOU UNIV
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