Multilayer ConvLSTM sea surface temperature prediction calculation method based on remote sensing data

A technology of remote sensing data and calculation methods, applied in the direction of prediction, calculation, data processing applications, etc., can solve problems such as poor results, achieve high prediction accuracy, quick use, and reduce manual effects

Pending Publication Date: 2021-03-23
SHANGHAI OCEAN UNIV
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Based on the traditional time series network, which does not combine time and space well,

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
  • Multilayer ConvLSTM sea surface temperature prediction calculation method based on remote sensing data
  • Multilayer ConvLSTM sea surface temperature prediction calculation method based on remote sensing data
  • Multilayer ConvLSTM sea surface temperature prediction calculation method based on remote sensing data

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0037] The embodiment of the present invention will be described in detail below with reference to the accompanying drawings: This example is implemented in the present invention, and the detailed embodiment and the specific operation process are given, but the scope of protection of the present invention is not limited to The embodiment is described.

[0038] With the growth of global technology, countries compete to launch their own remote sensing satellite. With the continuous increase in "Star", remote sensing information technology provides a multi-source and multi-scale time and space information for human beings, providing a wealth of information on marine temperature monitoring, forecasting and scientific research. Especially in the global ocean temperature data acquisition of long-term sequences, there is an advantage that the routine survey method cannot be replaced. How to effectively utilize the multi-source remote sensing data for long-term sequences to obtain high-pr...

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 a multilayer ConvLSTM sea surface temperature prediction and calculation method based on remote sensing data, belongs to the technical field of ocean remote sensing, combines the characteristics of a convolutional neural network and a recurrent neural network, can effectively process the batch problem of time sequence remote sensing data, predicts the seasonality and annuallong-term trend of sea surface temperature, and improves the prediction accuracy of sea surface temperature. Spatial information elements are displayed through time information, and spatial featuresof future sea surface temperature under periodic changes are predicted. The method comprises the following steps: receiving satellite sea surface temperature remote sensing data; preprocessing the remote sensing data; taking the normalized value as a label value of the generator; establishing a sample generator; and randomly selecting the data in the generator for training. According to the methodfor predicting the sea surface temperature based on the remote sensing data, the batch problem of the time sequence remote sensing data can be effectively solved, and the seasonality and the annual long-term trend of the sea surface temperature can be predicted.

Description

technical field [0001] The invention relates to the technical field of marine remote sensing, in particular to a multi-layer ConvLSTM sea surface temperature prediction calculation method based on remote sensing data. Background technique [0002] Sea temperature is one of the most fundamental environmental parameters of the ocean. Seawater temperature has a wide range of applications in fishery resources, monitoring of marine environmental pollution, ocean dynamics, and air-sea interaction. The measurement of sea surface temperature usually includes on-site measurement and satellite remote sensing. The on-site measurement data mainly comes from ship measurements and measurements from fixed or mobile buoy networks. These data play a key role in correcting satellite data and providing a large amount of measured temperature data. However, its coverage is limited, and the seawater temperature data obtained are only a few points or sections, so it is impossible to realize the s...

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): G06Q10/04G06N3/04G06N3/08
CPCG06Q10/04G06N3/049G06N3/08G06N3/045
Inventor 韩震张雪薇周玮辰
Owner SHANGHAI OCEAN UNIV
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