Determination of risky areas using sustainable indicators in urban transformation

In order to establish a region as a living space and to create the concept of a city or to develop an existing city by meeting its needs, it is necessary to take into account the physical and geographical situation of that region, its ground conditions, nature and its ties with other cities and settlements. In the context of spatial planning, meeting all needs and achieving developmental goals depends on the correct zoning planning and activities to be carried out in this field. When settlement is ensured in cities with zoning plans prepared for correct and sustainable urban life, a balanced, healthy, orderly and aesthetic urban life is created with housing areas, health areas, educational facilities, commercial and industrial centers, socio-economic living areas. In addition to all these, even zoning plans prepared and implemented with long-term projections, where spatial planning is done correctly, may become inadequate over time, may not keep up with the conditions of developing urban life, or the existing urban fabric may age and deteriorate. On the other hand, the danger of natural disasters may arise as a result of natural events such as earthquakes, floods and landslides, especially in terms of geology and geophysics sciences. For these reasons, existing urban planning, zoning plans and practices may become inadequate over time, and these areas may require change or transformation. These negative situations of places that have moved away from planned urbanization targets can only be compensated with the right urban regeneration planning and implementation strategies. In this thesis, a sustainable indicator system has been created for the most accurate identification of urban regeneration areas. Weighted importance coefficients of the indicators were calculated by AHP method. Then, a fuzzy logic based scoring formula was developed and indicator coefficients and area numerical data coefficients were used in this formula. According to the resulting score, it was determined whether an area needs urban transformation or not, and if so, the level of this transformation need was determined.