2020
DOI: 10.3390/ijgi9040263
|View full text |Cite
|
Sign up to set email alerts
|

Household Level Vulnerability Analysis—Index and Fuzzy Based Methods

Abstract: Coastal vulnerability assessment due to climate change impacts, particularly for sea level rise, has become an essential part of coastal management all over the world. For the planning and implementation of adaptation measures at the household level, large-scale analysis is necessary. The main aim of this research is to investigate and propose a simple and viable assessment method that includes three key geospatial parameters: elevation, distance to coastline, and building footprint area. Two methods are propo… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
1
0

Year Published

2020
2020
2023
2023

Publication Types

Select...
3
1

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(1 citation statement)
references
References 33 publications
0
1
0
Order By: Relevance
“…This special issue explores some of them, with challenging ideas facing different components of spatial patterns related to ecological processes and the published articles are selected and extended versions from the Gi4DM Conference in 2019 in Prague, Czech Republic. Articles [5][6][7] deal with sea-level rise. In the last decades, forest fires became a major disaster phenomenon and Luis Paduva [8] developed some innovative techniques such as UAV-borne observations and compared them with sentinel data.…”
mentioning
confidence: 99%
“…This special issue explores some of them, with challenging ideas facing different components of spatial patterns related to ecological processes and the published articles are selected and extended versions from the Gi4DM Conference in 2019 in Prague, Czech Republic. Articles [5][6][7] deal with sea-level rise. In the last decades, forest fires became a major disaster phenomenon and Luis Paduva [8] developed some innovative techniques such as UAV-borne observations and compared them with sentinel data.…”
mentioning
confidence: 99%