Use of Mamdani Fuzzy Algorithm for Multi-Hazard Susceptibility Assessment in a Developing Urban Settlement (Mamak, Ankara, Turkey)

Bibliographic Data

ID22033387
AuthorsTuğçe YANAR (0000-0001-7998-1793, Hacettepe University), Sultan Kocaman (0000-0002-2775-7914, Hacettepe University, corresponding author), Candan Gökçeoğlu (0000-0003-4762-9933, Hacettepe University)
Year2020
Volume9
Issue2
Pages114
Publication date2020-02-19
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi9020114
OpenAlexW3008858930
LanguageEN
Citations received6
References cited73

Urban areas may be affected by multiple hazards, and integrated hazard susceptibility maps are needed for suitable site selection and planning. Furthermore, geological–geotechnical parameters, construction costs, and the spatial distribution of existing infrastructure should be taken into account for this purpose. Up-to-date land-use and land-cover (LULC) maps, as well as natural hazard susceptibility maps, can be frequently obtained from high-resolution satellite sensors. In this study, an integrated hazard susceptibility assessment was performed for a developing urban settlement (Mamak District of Ankara City, Turkey) considering landslide and flood potential. The flood susceptibility map of Ankara City was produced in a previous study using modified analytical hierarchical process (M-AHP) approach. The landslide susceptibility map was produced using the logistic regression technique in this study. Sentinel-2 images were employed for generating LULC data with the random forest classification method. Topographical derivatives obtained from a high-resolution digital elevation model and lithological parameters were employed for the production of landslide susceptibility maps. For the integrated hazard susceptibility assessment, the Mamdani fuzzy algorithm was considered, and the results are discussed in the present study. The results demonstrate that multi-hazard susceptibility assessment maps for urban planning can be obtained by combining a set of expert-based and ensemble learning methods

Analytic hierarchy process · Cartography · Civil engineering · Data mining · Flood myth · Geographic information system · Geography · Geomorphology · Hazard · Land cover · Land use · Landslide · Meteorology · Natural hazard · Operations research · Remote sensing · Computer Science · Engineering · Environmental Science · Flood Risk Assessment and Management · Geotechnical Engineering and Analysis · Landslides and related hazards · Geology

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