FY-3D infrared hyperspectral cloud detection method based on extreme random tree

A cloud detection and random tree technology, applied in the fields of machine learning and satellite remote sensing, can solve problems such as difficult threshold setting, high memory cost and computing time cost, and achieve low storage cost, high practical application value, and high accuracy Effect

Active Publication Date: 2021-03-09
NAT UNIV OF DEFENSE TECH
View PDF8 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, the multi-channel threshold method proposed based on the physical characteristics of clouds is applied to most commercial satellite infrared sounders, but many cloud detections have multiple thresholds, and it is difficult to set an appropriate

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • FY-3D infrared hyperspectral cloud detection method based on extreme random tree
  • FY-3D infrared hyperspectral cloud detection method based on extreme random tree
  • FY-3D infrared hyperspectral cloud detection method based on extreme random tree

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment

[0078] 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 has developed into a typhoon at 16:00 on September 3, and has a tendency to further intensify. It developed into a strong typhoon on September 4 and quickly developed into a super typhoon.

[0079] Such as Figure 4 and Figure 5 As shown, it is the test result of the No. 10 typhoon "Poseidon" in 2020 at 16:40 on September 3. Figure 4 Indicates the observation results of mersi L2 level cloud detection products at 16:40, where 0 means definite cloud, 1 means possible cloud, 2 means possible clear sky, 3 means sure clear sky, and 4 means undetermined. Figure 5 Indicates the prediction result of the extreme random tree model, the input is the full-channel radiation data of 16:40 HIRAS, and the output is the cloud label corresponding to the hairs pixel. Where a represents a certain cloud, and b re...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an FY-3D infrared hyperspectral cloud detection method based on an extreme random tree, and relates to the technical field of satellite remote sensing. According to the method,HIRAS and MERSI carried on FY-3D are used for continuously observing data of the earth, time matching is conducted on two data files, space matching is conducted on pixels of two instruments, cloud labels of HIRAS pixels are determined through the cloud labels of the matched MERSI pixels, HIRAS data with the cloud labels are obtained, and a training data set of an extreme random tree model is formed; a data set is trained by using an extreme random tree algorithm, the performance of the model is checked by using a test data set, and finally the extreme random tree model is applied with bettercloud detection performance obtained by training to cloud detection processing of YF-3D infrared hyperspectral data. The cloud detection method is short in cloud detection time, low in cost and highin cloud detection classification accuracy.

Description

technical field [0001] The present invention relates to the field of satellite remote sensing technology, in particular to a decision tree-based integrated learning method in the field of machine learning—extreme random tree algorithm, combined with the method of detecting clouds in the field of view of HIRAS by using infrared hyperspectral data of FY-3D satellite HIRAS instrument . Background technique [0002] Infrared hyperspectral data is an important observational data for modern numerical weather prediction systems. Assimilating infrared hyperspectral data into a near-model system can effectively improve the forecasting level. Water droplets and ice crystals in clouds absorb infrared radiation so effectively that satellite infrared detectors cannot detect infrared radiation from the atmosphere below the clouds and the surface. In addition, it is difficult for current radiative transfer observation operators to accurately simulate the radiative effect of clouds. There...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/13G06F18/214
Inventor 史华湘余意张卫民罗藤灵张琪银福康马烁段博恒
Owner NAT UNIV OF DEFENSE TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap