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Yayın Landscape ecological evaluation of cultural patterns for the Istanbul urban landscape(MDPI, 2022-12) Aksu, Gül Aslı; Tağıl, Şermin; Musaoğlu, Nebiye; Seyek Canatanoğlu, Emel; Uzun, AdnanWith the widespread population growth in cities, anthropogenic influences inevitably lead to natural disturbances. The metropolitan area of Istanbul, with its rapid urbanization rate, has faced intense pressure regarding the sustainability of urban habitats. In this context, landscapes comprising patches affected by various disturbances and undergoing temporal changes must be analyzed, in order to assess city-related disturbances. In this study, the main objective was to understand how urbanization changed the function of the spatial distribution of the urban mosaic and, more specifically, its relationship with the size, shape, and connection among land-use classes. For this purpose, we took Besiktas, a district of Istanbul, as the study area. We evaluated the landscape pattern of the urban environment in two stages. First, we used medium-resolution satellite imagery to reveal the general interactions in the urbanization process. Landscape- and class-level landscape metrics were selected to quantify the landscape connectivity, and the distances between classes (green areas and artificial surfaces), patterns, and processes, using five satellite images representing a time span of 51 years (1963, 1984, 1997, 2005, and 2014). The general landscape structure was examined by looking at the temporal–spatial processes of artificial surface and green areas obtained from these medium-resolution satellite images. The trends in selected landscape-level metrics were specified and discussed through the use of a moving window analysis. We then used Pleiades high-resolution satellite imagery (2015) to analyze the landscape structure in more detail. This high-resolution base image allows us to recognize the possibility of classifying basic cultural landscape classes. The findings regarding the spatial arrangement of each class in the areas allocated to 14 cultural landscape classes were interpreted by associating them with the landscape functions. Finally, particulate matter (PM10) concentration data were collected and evaluated as an ecological indicator, in order to reveal the relationships between landscape structure and landscape function. In short, we first evaluated the whole landscape structure using medium-resolution data, followed by the classification of cultural landscapes using high-resolution satellite imagery, providing a time-effective—and, therefore, essential—auxiliary method for landscape evaluation. This two-stage evaluation method enables inferences to be made that can shed light on the landscape functions in an urban environment based on the landscape structure.Yayın A decision making support tool for selecting green building certification credits based on project delivery attributes(Pergamon-Elsevier Science Ltd, 2017-12) Seyis Kazazoğlu, Senem; Ergen Pehlevan, EsinThe Green Building (GB) certification process embodies detailed requirements and specifications that lead to additional tasks for project teams, which increases complexity levels of the entire project delivery process. Previous studies show that if the GB certification credits to be fulfilled are selected without considering project team attributes, then elevated levels of time, money, and labor could get wasted while attempting to meet the additional requirements of GB certification. The aim of this study is to develop a multi-attribute decision making (MADM) support tool to be used by GB experts to select the appropriate GB certification credits based on the project team attributes. The developed framework with relative weights assigned via the Delphi method was used to perform the MADM analysis, which employs the hybrid use of the Multi Attribute Utility Technique (MAUT) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). This paper presents the developed MADM tool (i.e., GB-CS tool) and the relative weights of the attributes that were determined following expert opinions. To validate the tool, a case study was conducted at a LEED-registered residential project. The results show that the GB-CS Tool was successful in ranking the GB certification credits to be selected. This hybrid MADM tool can be used for preventing disruptions and bottlenecks in GB project delivery processes by assisting the owners/GB consultants in effectively selecting suitable GB certification credits based on the project team attributes. Thus, with the assistance of the GB-CS tool, root causes of waste can be mitigated in the GB project delivery process, decreasing associated hidden costs.Yayın Critical digital data enabling traceability for smart honey value chains(Taylor and Francis Ltd., 2025-02) Ziemba, Ewa Wanda; Maruszewska, Ewa Wanda; Karmanska, Anna; Aydın, Mehmet Nafiz; Aydın, ŞahinData analysis and sharing are becoming increasingly important in creating value within food supply chains, including honey value chains. While some data is readily shared between supply chain actors, unlocking further benefits requires additional investments in digital data capturing, particularly for value-based claims such as sustainability, equity, and traceability from hives to customers. This study aims to identify critical digital data necessary for smart honey value chains to ensure traceability and transparency while fostering trust among beekeepers, intermediaries, and consumers. Semi-structured interviews with 30 beekeeping experts were conducted to explore their perspectives. The analysis identified four critical categories of data—beekeeper data, apiary data, honey data, and apiary practices data—encompassing 21 specific data points essential for ensuring transparency, traceability, and trust. These findings provide novel insights into the digital data requirements necessary to support the honey industry’s evolving needs for transparent and traceable value chains.
