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

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 fo...

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Bibliographic Details
Published in:	ISPRS international journal of geo-information , Vol.9 (2), p.114
Main Authors:	Yanar, Tugce, Kocaman, Sultan, Gokceoglu, Candan
Format:	Article
Language:	eng
Subjects:	Algorithms Analytic hierarchy process Climate change Construction costs developing urban settlements Digital Elevation Models Disasters Earthquakes flood Flood mapping Floods Forest & brush fires Gene mapping Geographic information systems Geological mapping Geomorphology Hazard assessment Hazards Heavy construction High resolution Image classification Infrastructure Land cover Land use Land use planning landslide Landslides Landslides & mudslides Lithology logistic regression m-ahp mamdani fuzzy algorithm multi-hazard Parameters Resolution Risk assessment Seismic engineering Site selection Spatial analysis Spatial distribution Susceptibility susceptibility mapping Topography Urban areas Urban planning
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Summary:	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.
ISSN:	2220-9964 2220-9964