Survey of computer vision-based natural disaster warning systems

被引：33

作者：

Ko, ByoungChul ^{[1
]}

Kwak, Sooyeong ^{[2
]}

机构：

[1] Keimyung Univ, Dept Comp Engn, Taegu 704701, South Korea

[2] Hanbat Natl Univ, Dept Elect & Control Engn, Taejon 305719, South Korea

来源：

OPTICAL ENGINEERING | 2012年 / 51卷 / 07期

基金：

新加坡国家研究基金会;

关键词：

natural disaster; remote sensing; vision sensor; wildfire detection; water level detection; coastal zone monitoring; landslide detection; WILDFIRE DETECTION; MANAGEMENT; FLAMES;

D O I：

10.1117/1.OE.51.7.070901

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

With the rapid development of information technology, natural disaster prevention is growing as a new research field dealing with surveillance systems. To forecast and prevent the damage caused by natural disasters, the development of systems to analyze natural disasters using remote sensing geographic information systems (GIS), and vision sensors has been receiving widespread interest over the last decade. This paper provides an up-to-date review of five different types of natural disasters and their corresponding warning systems using computer vision and pattern recognition techniques such as wildfire smoke and flame detection, water level detection for flood prevention, coastal zone monitoring, and landslide detection. Finally, we conclude with some thoughts about future research directions. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.OE.51.7.070901]

引用

页数：11

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