FY-3D infrared hyperspectral cloud detection method based on logistic regression

A FY-3D, logistic regression technology, applied in the field of satellite remote sensing and machine learning, can solve the problems of large image classification network, high computing cost, inconvenient to join the business assimilation system, etc., to achieve high accuracy, low cost, high practical application effect of value

Active Publication Date: 2021-05-07
NAT UNIV OF DEFENSE TECH
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Problems solved by technology

However, this method uses high-resolution cloud images as feature inputs, which also requires high computational costs
In addition, the typical image classification network is relatively large, which is not convenient to add to the business assimilation system of the numerical model.

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  • FY-3D infrared hyperspectral cloud detection method based on logistic regression
  • FY-3D infrared hyperspectral cloud detection method based on logistic regression
  • FY-3D infrared hyperspectral cloud detection method based on logistic regression

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specific Embodiment

[0105] In order to better understand the technical content of the present invention, the forecast results of the No. 10 typhoon in 2020 - "Fengshen" are specially cited. The typhoon developed into a typhoon on September 3 and tended to intensify further. It developed into a strong typhoon on September 4 and quickly developed into a super typhoon.

[0106] As shown in Figure 4(a) and Figure 4(b), it is the test result of the No. 10 typhoon "Poseidon" in 2020 at 04:10 (UT) on September 3. Figure 4(a) shows the observation results of MERSI L2 level cloud detection products at 04:10, where 0 indicates definite cloud, 1 indicates possible cloud, 2 indicates possible clear sky, 3 indicates definite clear sky, and 4 indicates undetermined. Figure 4(b) shows the prediction results of the logistic regression model. Its input is the full-channel radiation data of 04:10 HIRAS, and the output is the cloud label corresponding to the HIRAS pixel, where 0 indicates a certain cloud and 1 indi...

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Abstract

The invention discloses an FY-3D infrared hyperspectral cloud detection method based on logistic regression, and relates to the technical field of satellite remote sensing. According to the method, a traditional cloud detection method based on an imager is utilized, a cloud detection section product of MERSI is matched with an HIRAS pixel, HIRAS data with a cloud tag is obtained, a training data set is formed, then the data set is trained by using a logistic regression algorithm, in the training process, a grid search method is adopted to select a proper logistic regression algorithm supernormal number, thereby obtaining a model parameter with best generalization performance; and finally, applying the logistic regression cloud detection model obtained by training to cloud detection processing of infrared hyperspectral data of YF-3D. The logistic regression cloud detection model can reach 0.97 classification accuracy, the prediction speed is about 50 times that of a traditional method, and good generalization performance is embodied.

Description

technical field [0001] The invention relates to the technical field of satellite remote sensing, in particular to a logical regression algorithm in the field of machine learning combined with a method for detecting clouds in the field of view of HIRAS by using infrared hyperspectral data of FY-3D satellite HIRAS instruments. Background technique [0002] Infrared hyperspectral data are important observational data for modern numerical weather prediction systems. The assimilation of infrared hyperspectral data is of great significance for effectively improving the level of numerical weather prediction. Water droplets and ice crystals in clouds can effectively absorb infrared radiation, making satellite infrared detectors unable to detect infrared radiation in the atmosphere below the clouds and on the surface. In addition, it is difficult for current radiative transfer observation operators to accurately simulate the radiative effect of clouds. Therefore, cloud contaminatio...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T17/00G06K9/62G06F17/11G06F17/15
CPCG06T17/00G06F17/11G06F17/15G06F18/24
Inventor 余意史华湘张卫民罗藤灵张琪王鹏飞吴建平王舒畅
Owner NAT UNIV OF DEFENSE TECH
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