Investigating socio-ecological vulnerability to climate change via remote sensing and a data-driven ranking algorithm

The necessity for extensive historical data, variables, and weight determination still presents challenges and complexity, notwithstanding the growth in research on socio-ecological vulnerability to climate change. In order to fill in these gaps, this study used China's Fujian Province as a cas...

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Bibliographic Details
Published in:	Journal of environmental management Vol. 347; p. 119254
Main Authors:	Ikhumhen, Harrison Odion, Fang, Qinhua, Lu, Shanlong, Meilana, Lusita, Raimundo Lopes, Namir Domingos
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.12.2023
Subjects:	algorithms autocorrelation case studies China Climate change coasts Data ranking algorithm decision making environmental management land use Remote sensing Socioecological indicators Socioecological vulnerability stakeholders United Nations Framework Convention on Climate Change vegetation China Climate change Data ranking algorithm Socioecological vulnerability Remote sensing Socioecological indicators
ISSN:	0301-4797, 1095-8630, 1095-8630
Online Access:	Get full text
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