Study on Heat Vulnerability Assessment Using Biotope Map: A Case Study of Suwon, Korea

2020 ◽  
Vol 11 (6-1) ◽  
pp. 629-641
Author(s):  
Kyung Il Lee ◽  
Sung Joo Lee ◽  
Namuun Tuvshinjargal ◽  
Eun Sun Lee ◽  
Gwan Gyu Lee ◽  
...  
Keyword(s):  
Vulnerability Assessment ◽  
Heat Vulnerability

Extreme heat vulnerability assessment in tropical region: a case study in Malaysia

2021 ◽  
pp. 1-15
Author(s):  
Nurfatin Izzati Ahmad Kamal ◽  
Zulfa Hanan Ash'aari ◽  
Ahmad Makmom Abdullah ◽  
Faradiella Mohd Kusin ◽  
Ferdaus Mohamat Yusuff ◽  
...  
Keyword(s):  
Vulnerability Assessment ◽  
Extreme Heat ◽  
Tropical Region ◽  
Heat Vulnerability

scholarly journals Fuzzy or Non-Fuzzy? A Comparison between Fuzzy Logic-Based Vulnerability Mapping and DRASTIC Approach Using a Numerical Model. A Case Study from Qatar

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1288
Author(s):  
Husam Musa Baalousha ◽  
Bassam Tawabini ◽  
Thomas D. Seers
Keyword(s):  
Fuzzy Logic ◽  
Numerical Model ◽  
Vulnerability Assessment ◽  
Anthropogenic Impacts ◽  
Groundwater Vulnerability ◽  
Vulnerability Mapping ◽  
Anthropogenic Contamination ◽  
Weighted Overlay ◽  
Vulnerability Maps

Vulnerability maps are useful for groundwater protection, water resources development, and land use management. The literature contains various approaches for intrinsic vulnerability assessment, and they mainly depend on hydrogeological settings and anthropogenic impacts. Most methods assign certain ratings and weights to each contributing factor to groundwater vulnerability. Fuzzy logic (FL) is an alternative artificial intelligence tool for overlay analysis, where spatial properties are fuzzified. Unlike the specific rating used in the weighted overlay-based vulnerability mapping methods, FL allows more flexibility through assigning a degree of contribution without specific boundaries for various classes. This study compares the results of DRASTIC vulnerability approach with the FL approach, applying both on Qatar aquifers. The comparison was checked and validated against a numerical model developed for the same study area, and the actual anthropogenic contamination load. Results show some similarities and differences between both approaches. While the coastal areas fall in the same category of high vulnerability in both cases, the FL approach shows greater variability than the DRASTIC approach and better matches with model results and contamination load. FL is probably better suited for vulnerability assessment than the weighted overlay methods.

Groundwater Vulnerability Assessment Through a Modified DRASTI-LU Framework: Case Study of Saiss Basin in Morocco

2021 ◽  
Author(s):  
Abdelhakim Lahjouj ◽  
Abdellah El Hmaidi ◽  
Ali Essahlaoui ◽  
M. J. B. Alam ◽  
Mohammed S. A. Siddiquee ◽  
...  
Keyword(s):  
Vulnerability Assessment ◽  
Groundwater Vulnerability ◽  
Groundwater Vulnerability Assessment

scholarly journals A Raster-Based Subdividing Indicator to Map Urban Heat Vulnerability: A Case Study in Sydney, Australia

2018 ◽  
Vol 15 (11) ◽  
pp. 2516 ◽  
Author(s):  
Wei Zhang ◽  
Phil McManus ◽  
Elizabeth Duncan
Keyword(s):  
High Heat ◽  
The Past ◽  
Urban Heat ◽  
Research Gap ◽  
Heat Vulnerability ◽  
Very High ◽  
Flexible Model ◽  
General Indicator ◽  
Sydney Australia

Assessing and mapping urban heat vulnerability has developed significantly over the past decade. Many studies have mapped urban heat vulnerability with a census unit-based general indicator (CGI). However, this kind of indicator has many problems, such as inaccurate assessment results and lacking comparability among different studies. This paper seeks to address this research gap and proposes a raster-based subdividing indicator to map urban heat vulnerability. We created a raster-based subdividing indicator (RSI) to map urban heat vulnerability from 3 aspects: exposure, sensitivity and adaptive capacity. We applied and compared it with a raster-based general indicator (RGI) and a census unit-based general indicator (CGI) in Sydney, Australia. Spatial statistics and analysis were used to investigate the performance among those three indicators. The results indicate that: (1) compared with the RSI framework, 67.54% of very high heat vulnerability pixels were ignored in the RGI framework; and up to 83.63% of very high heat vulnerability pixels were ignored in the CGI framework; (2) Compared with the previous CGI framework, a RSI framework has many advantages. These include more accurate results, more flexible model structure, and higher comparability among different studies. This study recommends using a RSI framework to map urban heat vulnerability in the future.

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