A remote sensing image-based inland water body blue-green algae classification and recognition method

A remote sensing image, classification and recognition technology, applied in the field of image processing, can solve the problem of inability to monitor the cyanobacteria on the lake surface in a timely and accurate manner, and achieve the effect of improving the accuracy and reducing the workload.

Inactive Publication Date: 2019-04-23
HOHAI UNIV
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Problems solved by technology

[0006] The traditional monitoring of cyanobacteria mainly focuses on the use of land water environment monitoring stations. Although this method can monitor t...

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  • A remote sensing image-based inland water body blue-green algae classification and recognition method
  • A remote sensing image-based inland water body blue-green algae classification and recognition method
  • A remote sensing image-based inland water body blue-green algae classification and recognition method

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Embodiment Construction

[0036] In order to further describe the technical features and effects of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0037] refer to Figure 1 to Figure 7 As shown, a classification and recognition method of inland water cyanobacteria based on remote sensing images,

[0038] figure 1 It is a schematic diagram of the artificial neuron mathematical model of the present invention, and each neuron unit is a simulation pattern of neuron cells in the biological neural network, which has the characteristics of multiple inputs and single output, and is a nonlinear element in the artificial neural network. then, figure 2 It is a schematic diagram of a three-layer BP neural network model in the present invention, and the BP neural network is composed of an input layer, one or more hidden layers and an input layer. After the above analysis, it is known that only one hidden laye...

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Abstract

The invention discloses a remote sensing image-based inland water body blue-green algae classification and recognition method, which comprises the following steps of 1) obtaining an optical remote sensing data source image, and processing the obtained data source image to obtain a pre-processed optical image capable of being recognized; 2) performing radiation calibration and atmospheric correction on the identifiable pre-processed optical image obtained in the step 1); and 3) establishing a deep neural network for extracting blue-green algae information of the water body by using the image obtained in the step 2) after over-radiation calibration and atmospheric correction, and identifying the blue-green algae information through the deep neural network. According to the method, the remotesensing image is introduced into monitoring of the blue-green algae, so that the problem of high cost, long time consumption and the like due to limited sampling frequency in a traditional method formanually collecting a water sample on site for water quality analysis are solved. The remote sensing image has the characteristics of high spatial coverage and high time resolution, and can well detect the lake blue-green algae bloom.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a remote sensing image-based classification and identification method for inland water cyanobacteria. Background technique [0002] LANDSAT US land series satellites are satellites that mainly transmit optical images. The main tasks are to investigate underground mineral deposits, marine resources and groundwater resources, monitor and assist in the management of agriculture, forestry, animal husbandry and water conservancy. The growth and landform of natural plants, inspect and forecast various serious natural disasters (such as earthquakes) and environmental pollution, take images of various targets, and draw various thematic maps (such as geological maps, landform maps, hydrological maps), etc. [0003] The Sentinel-2A satellite launched by the European Space Agency (ESA, European Space Agency) carries a multispectral imager, which can cover 13 spectral bands with a w...

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Application Information

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IPC IPC(8): G06K9/62G06N3/06G06N3/08
CPCG06N3/061G06N3/084G06F18/2413
Inventor 陈嘉琪吕吉明王健王娴珏胡居荣
Owner HOHAI UNIV
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