Time Series SAR Data Analysis And Application Research Based On Remote Sensing Cloud Platform

This article is aimed at the problem that lots of open source SAR data cannot be quickly used.Based on Google Earth Engine,a typical remote sensing cloud platform,the time series of SAR data covering all over the world is used to obtain key scientific information,such as sea routes,flooded areas,and new time-series In SAR processing modes1.Detecting sea routes based on remote sensing cloud platform.Choosing and filtering the preprocessed synthetic aperture radar(SAR)image to obtain the first image subset;Synthetic Aperture Radar(SAR)images in the first image subset to obtain ship and route information and calculate preliminary route maps;calculate land and sea interference points and perform image masking to obtain mask layers;The mask layers are combined to generate a water route map.2.A method for automatic extraction of flood-affected areas using data and functions of existing cloud platforms was researched.It mainly adopts SAR change monitoring technology,Google Geographic Cloud Computing technology of GEE(Google Earth Engine)platform,and spatial analysis and processing technology of Arc GIS software.The mask processing is used to eliminate interference in areas such as mountain waters,and then the difference method and morphological filtering are used.Select the water body range,and finally visualize the affected area on the cloud platform and export it.This method can greatly shorten the mapping time to provide the latest disaster distribution images.It has important contributions to the government's macro grasp of the disaster situation,the strategic layout of disaster relief,and the estimation of economic losses after the disaster.It has great scientific significance and social value.3.Based on the problem of improving the efficiency of In SAR deformation monitoring,taking advantage of remote sensing cloud services,relying on GEE,the new In SAR mode of the joint cloud platform is studied.This part focuses on cloud platform remote sensing data integration methods,multi-source data high-coherence point recognition models,and time series In SAR analysis methods.Through the above-mentioned work,a new In SAR time series processing method combined with remote sensing cloud services is established,which will provide new attempts and ideas for efficient and convenient large-scale In SAR deformation monitoring.The last part is a time series In SAR processing case of the new In SAR deformation monitoring model supporting the joint cloud platform constructed in the third part.Taking the the Nepal earthquake as an example,the paper studied settlement details of the post-earthquake.In short,by using massive SAR data on GEE,a typical remote sensing cloud platform,this paper studies global sea route detection methods,rapid flood detection methods,and a new In SAR deformation monitoring model combined with cloud platforms,which verifies the practicality of remote sensing cloud platforms.And high value,and believe that the rise of such platforms will bring fundamental changes to existing remote sensing methods.