Disaster Monitoring of Satellite Image Processing Using Progressive Image Classification  

作　　者：Romany F.Mansour Eatedal Alabdulkreem 

机构地区：[1]Department of Mathematics,Faculty of Science,New Valley University,El-Kharga,72511,Egypt [2]Department of Computer Science,College of Computer and Information Sciences,Princess Nourah bint Abdulrahman University,P.O.Box 84428,Riyadh 11671,Saudi Arabia

出　　处：《Computer Systems Science & Engineering》2023年第2期1161-1169,共9页计算机系统科学与工程（英文）

基　　金：funded by Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia,under grant No.(PNURSP2022R161).

摘　　要：The analysis of remote sensing image areas is needed for climate detec-tion and management,especially for monitoringflood disasters in critical environ-ments and applications.Satellites are mostly used to detect disasters on Earth,and they have advantages in capturing Earth images.Using the control technique,Earth images can be used to obtain detailed terrain information.Since the acquisi-tion of satellite and aerial imagery,this system has been able to detectfloods,and with increasing convenience,flood detection has become more desirable in the last few years.In this paper,a Big Data Set-based Progressive Image Classification Algorithm(PICA)system is introduced to implement an image processing tech-nique,detect disasters,and determine results with the help of the PICA,which allows disaster analysis to be extracted more effectively.The PICA is essential to overcoming strong shadows,for proper access to disaster characteristics to false positives by operators,and to false predictions that affect the impact of the disas-ter.The PICA creates tailoring and adjustments obtained from satellite images before training and post-disaster aerial image data patches.Two types of proposed PICA systems detect disasters faster and more accurately(95.6%).

关 键 词：CLUSTERING SEGMENTATION progressive image classification algorithm satellite image disaster detection 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]