Environmental Remote Sensing in Flooding Areas - A Case Study of Ayutthaya, Thailand (Hardcover, 1st ed. 2021)

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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Release date:	December 2020
First published:	2021
Authors:	Chunxiang Cao • Min Xu • Patcharin Kamsing • Sornkitja Boonprong • Peera Yomwan • Apitach Saokarn
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	148
Edition:	1st ed. 2021
ISBN-13:	978-981-15-8201-1
Categories:	Books > Professional & Technical > Environmental engineering & technology > Environmental monitoring Books > Medicine > General issues > Public health & preventive medicine > Epidemiology & medical statistics Books > Medicine > Other branches of medicine > Environmental medicine > General Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Geographical information systems (GIS) Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Remote sensing Promotions
LSN:	981-15-8201-7
Barcode:	9789811582011

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