BP neural network microwave remote sensing soil moisture inversion method optimized by considering firefly algorithm

A BP neural network and firefly algorithm technology, applied in the field of microwave remote sensing soil moisture inversion, can solve problems such as slow convergence speed and easy to fall into extreme values

Inactive Publication Date: 2021-06-04
INST OF AGRI RESOURCES & REGIONAL PLANNING CHINESE ACADEMY OF AGRI SCI +2
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Problems solved by technology

However, the neural network model has certain defects, such as slow convergence speed, easy to fall into extreme values, etc.

Method used

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  • BP neural network microwave remote sensing soil moisture inversion method optimized by considering firefly algorithm
  • BP neural network microwave remote sensing soil moisture inversion method optimized by considering firefly algorithm
  • BP neural network microwave remote sensing soil moisture inversion method optimized by considering firefly algorithm

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Embodiment Construction

[0034] The present invention will be described in detail below in conjunction with specific implementation examples.

[0035] Step 1: Obtain the corresponding ALOS-2L-band radar level 1.1 remote sensing image in the study area, and preprocess the image at the same time to obtain the total backscatter coefficient, and simultaneously obtain the CLDAS-V2.0 soil moisture data for the model at the same time calculation and verification;

[0036] Step 101. Obtain the ALOS-2L-band radar 1.1-level dual-polarization (HH and HV) remote sensing image corresponding to the Qianxinan area of ​​Guizhou Province. The image acquisition date is August 2, 2020. The radar image is oblique range imaging. During the imaging process Speckle noise and image distortion appear. Use the SARscape plug-in in ENVI5.3 to preprocess the radar image. The processing process includes: 1. Data import to obtain SLC data; 2. Multi-view and filter processing to remove SAR image speckle noise; 3. Radiation Calibrat...

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Abstract

The invention discloses a BP neural network microwave remote sensing soil moisture inversion method optimized by considering a firefly algorithm, and the method comprises the following steps: 1, obtaining a corresponding ALOS-2L waveband radar 1.1-level remote sensing image in a research region, carrying out the preprocessing of the image, obtaining a total backscattering coefficient, and simultaneously and synchronously acquiring CLDAS-V2.0 soil moisture data in the same time for model calculation and verification; 2, the research area being a vegetation coverage area, according to a water cloud (WCM) model, removing the influence of vegetation in the research area on the soil backscattering coefficient, obtaining the soil backscattering coefficient, meanwhile, obtaining Landsat-8 optical data in the same area within the same or similar time, calculating related vegetation indexes through band operation after preprocessing, and providing data support for the water cloud model; and 3, according to a BP neural network topological structure, establishing a corresponding data set for the soil backscattering coefficient obtained in the step 2 and CLDAS soil moisture data, and optimizing the BP neural network by using a firefly algorithm so as to perform soil moisture inversion.

Description

technical field [0001] The invention belongs to the research on microwave remote sensing soil moisture inversion, in particular to a microwave remote sensing soil moisture inversion method considering firefly algorithm optimization BP neural network. Background technique [0002] Soil moisture is a key research parameter in disciplines such as agriculture, hydrology and meteorology. The remote sensing method to retrieve soil moisture can be subdivided into microwave remote sensing and optical remote sensing. Optical remote sensing uses the reflection spectrum information of soil to analyze soil moisture content, but optical remote sensing has its own limitations, it is difficult to obtain the value of soil moisture parameters, especially affected by weather such as light, temperature and cloud cover, and the inversion of soil moisture has a large error . The penetration of microwave remote sensing is relatively strong, and the interference caused by weather conditions such...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06F17/10G06N3/00G06N3/04G06N3/08
CPCG06F30/27G06F17/10G06N3/006G06N3/084G06N3/044
Inventor 高懋芳高雅张蕙杰李顺国冷佩段四波
Owner INST OF AGRI RESOURCES & REGIONAL PLANNING CHINESE ACADEMY OF AGRI SCI
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