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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Vydáno v:	Journal of environmental management Ročník 347; s. 119254
Hlavní autoři:	Ikhumhen, Harrison Odion, Fang, Qinhua, Lu, Shanlong, Meilana, Lusita, Raimundo Lopes, Namir Domingos
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.12.2023
Témata:	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
On-line přístup:	Získat plný text
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