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Remote Sensing for Integrated Disaster Risk Management

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (15 January 2023) | Viewed by 25332

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Special Issue Editor

Prof. Dr. Jason Levy

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Guest Editor

Disaster Preparedness and Emergency Management, University of Hawaii, 2540 Dole Street, Honolulu, HI 96822, USA
Interests: epidemiology and prevention of congenital anomalies; psychosis and affective psychosis; cancer epidemiology and prevention; molecular and human genome epidemiology; evidence synthesis related to public health and health services research
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Special Issue Information

Dear Colleagues,

This Special Issue focuses on advances in remote sensing and GIS for hazards analysis, emergency studies, and disaster risk reduction in the age of intelligence. Governments around the world are investing in remote sensing for integrated all-hazard management in the age of artificial intelligence. This Special Issue will focus on technological transformations and ways in which advances in GIS and remote sensing can reduce disaster risk and increase integrated, all hazards, and comprehensive emergency management. This Special Issue also emphasizes that reducing disaster risk and investing in remote sensing technology can boost overall economic productivity, save lives, minimize damage to critical infrastructure, and revitalize the economy.

Prof. Dr. Jason Levy
Guest Editor

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Keywords

integrated disaster risk reduction
all hazards emergency management
intelligent systems
remote sensing for disaster studies
GIS for hazards analysis
age of intelligence

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Published Papers (1 paper)

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21 pages, 1352 KiB

Open AccessFeature PaperReview

Remote Sensing Methods for Flood Prediction: A Review

by Hafiz Suliman Munawar, Ahmed W. A. Hammad and S. Travis Waller

Sensors 2022, 22(3), 960; https://doi.org/10.3390/s22030960 - 26 Jan 2022

Cited by 102 | Viewed by 24408

Abstract

Floods are a major cause of loss of lives, destruction of infrastructure, and massive damage to a country’s economy. Floods, being natural disasters, cannot be prevented completely; therefore, precautionary measures must be taken by the government, concerned organizations such as the United Nations Office for Disaster Risk Reduction and Office for the coordination of Human Affairs, and the community to control its disastrous effects. To minimize hazards and to provide an emergency response at the time of natural calamity, various measures must be taken by the disaster management authorities before the flood incident. This involves the use of the latest cutting-edge technologies which predict the occurrence of disaster as early as possible such that proper response strategies can be adopted before the disaster. Floods are uncertain depending on several climatic and environmental factors, and therefore are difficult to predict. Hence, improvement in the adoption of the latest technology to move towards automated disaster prediction and forecasting is a must. This study reviews the adoption of remote sensing methods for predicting floods and thus focuses on the pre-disaster phase of the disaster management process for the past 20 years. A classification framework is presented which classifies the remote sensing technologies being used for flood prediction into three types, which are: multispectral, radar, and light detection and ranging (LIDAR). Further categorization is performed based on the method used for data analysis. The technologies are examined based on their relevance to flood prediction, flood risk assessment, and hazard analysis. Some gaps and limitations present in each of the reviewed technologies have been identified. A flood prediction and extent mapping model are then proposed to overcome the current gaps. The compiled results demonstrate the state of each technology’s practice and usage in flood prediction. Full article

(This article belongs to the Special Issue Remote Sensing for Integrated Disaster Risk Management)

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