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Environmental Remote Sensing in Flooding Areas

A Case Study of Ayutthaya, Thailand

Chunxiang Cao

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Paperback / softback
14 December 2021
$184.00
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This book introduces flood inundation area and flood risks assessment based on a comprehensive monitoring system using remote sensing and geographic information system technologies. Taking the 2011 flood disaster of Ayutthaya in Thailand as an example, it presents a flood intrusion zone identification method based on remote sensing technology, spatial information technology and geographic information system for flood disaster monitoring and early warning system. It introduces the study area and data, vegetation index, improved support vector machine and flood intrusion zone identification method. It also analyzes the flood remote sensing parameters and waterborne diseases, method of risk assessment of waterborne disease outbreak, waterborne disease outbreak risk monitoring based on backpropagation neural network and its expert system. It not only promotes a new interdisciplinary approach both in public health and space information technology, but also greatly supports decision makers in disaster reduction.

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$184.00
Ships in 5–7 business days
Hurry up! Current stock:

Environmental Remote Sensing in Flooding Areas

$184.00

Description

This book introduces flood inundation area and flood risks assessment based on a comprehensive monitoring system using remote sensing and geographic information system technologies. Taking the 2011 flood disaster of Ayutthaya in Thailand as an example, it presents a flood intrusion zone identification method based on remote sensing technology, spatial information technology and geographic information system for flood disaster monitoring and early warning system. It introduces the study area and data, vegetation index, improved support vector machine and flood intrusion zone identification method. It also analyzes the flood remote sensing parameters and waterborne diseases, method of risk assessment of waterborne disease outbreak, waterborne disease outbreak risk monitoring based on backpropagation neural network and its expert system. It not only promotes a new interdisciplinary approach both in public health and space information technology, but also greatly supports decision makers in disaster reduction.

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