Kentsel Planlama Alanları için Karar Verme Sürecinde Yönlendirici Bileşenler: Kent İçi Lojistik Alanlar

Günümüzde, kentsel nüfus artışının büyüklüğünü ve bunun kentleşme üzerindeki etkilerini ortaya çıkarmak, kentsel dönüşüm alanlarının belirlenmesinde başlıca yönlendirici bileşendir. Çeşitli aktivite alanlarının planlaması sürecinde kentsel öneme sahip alanların belirlenmesi ön plana çıkmaktadır. Bununla birlikte, hem bu alanlar hem de lojistik merkezler, alt ölçekli arazi kullanım planlamasının eksikliğine dayalı olarak kentsel gelişim alanlarında yer almaktadır. Bu durum arazi kullanımına uygunluk konusunda ihtiyaç duyulan spesifik bilgilere erişimi zorlaştırmaktadır. Bu çalışmada kent içi lojistik alanların kentsel dokuya konumsal entegrasyonuna yanıt vermek için karar verme sürecine yönelik kavramsal veri modeli geliştirilmektedir. Ayrıca, bu modelin konumsal modellerinin, kentsel morfolojinin bir parçası olarak ön plana çıkan kentsel dönüşüm projeleri ile nasıl uygulanabileceği vurgulanmaktadır. Bahsedilen lojistik alanların yeniden tahsisinin, politika odaklı arazi kullanımı dahilinde kentsel gelişim ile bütüncül olarak değerlendirilerek uygulanması gerekmektedir. Modelin sürdürülebilirliği için fiziksel ve çevresel dinamiklerle sosyo-ekonomik bileşenlerin etkileşiminin model bünyesinde temsil edilmesi önerilmektedir.

The Key Drivers on Decision Making for Urban Planning Sites: Inner City Logistic Fields

Today, uncovering magnitude of population growth in cities and its effects on urbanization are major driver for understanding of the requirements of assisting urban regeneration sites. It has growing interests on identifying the hotspots over planning for the various amenities fields. However, both these areas and the logistic centers are located in urban internal fabrics even if without sub-scale land use planning. It is hard to provide the needed customized information on land use suitability. It was proposed building conceptual geo-data model for decision-making process to respond the spatial integration of inner-city logistic fields to urban fabric. Further it is highlighted how geo-spatial patterns of this model could be applied with urban regeneration project that has growing considerations as part of urban morphology. And re-allocation of these logistic fields need to be integrated more transformative drivers for adaptation to growing city-size within policy driven land use. To better outcomes a comprehensive perspective should be included in model for representation of socio-economic concerns collaboration with physical and environmental dynamics. This model provides information to enable effective decision support for the conversion of the logistic areas as a priority with respect to other urban thematics concerns in more cities.

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