Browsing by Author "Ustaoglu, Eda"

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Estimation of Economic Costs of Air Pollution From Road Vehicle Transportation in Turkey
(2024) Ustaoglu, Eda
Hava kirliliğinin sosyo-ekonomik ve çevresel etkilerinin değerlendirilmesi, eylem önceliklerini belirlemek için bir temel oluşturan kirlilik kontrol stratejilerinin maliyet-fayda analizi için çok önemlidir. Bu makale, hava kalitesi modelleme, mühendislik ve ekonomiyi birleştiren entegre bir değerlendirme metodolojisi kullanarak karayolu taşımacılığıyla ilgili hava kirleticilerinin neden olduğu toplam dışsal maliyetlerin tahminine odaklanmaktadır. Karayolu taşımacılığından kaynaklanan emisyonların hesaplanmasında emisyon faktörleri ve ulaşım ağı özellikleri kullanılmış olup uluslararası örnek çalışmalardan uyarlanan ekonomik değerleme yaklaşımları takip edilerek Türkiye’deki hava kirliliğinin ekonomik maliyetinin hesaplanmasında kullanılmıştır. Sonuçlar, 2018 yılında Türkiye’de hava kirliliğinin toplam dışsal maliyetinin CO emisyonları için hesaplanan 37,500 avro ile NOx emisyonları için üst sınır olarak hesaplanan 2,686 milyon avro arasında değiştiğini gösterdi. CO2 emisyonlarının sosyal maliyetleri ile ilgili olarak, değerler 31 milyon avro ile 1,427 milyon avro arasında değişmektedir. Bunlardan ilki düşük değerli tahmini, ikincisi ise yüksek değerli tahmini temsil etmektedir. Bulgular karayolu taşımacılığından kaynaklanan emisyonların çevre ve toplum üzerindeki etkisinin Türkiye’de önemli olabileceğini göstermektedir. Bu nedenle, ulaşım emisyonlarını azaltmak ve sosyo-ekonomik refahı sürdürmek için bazı düzenlemeler gereklidir.
Estimation of Demand for Urban Land Uses: A Case Study of Türkiye
(2024) Ustaoglu, Eda
Geçtiğimiz yıllar içerisinde, farklı yerler ve bölgeler hızlı bir kentleşmeyle karşı karşıya kalmıştır. Hızlı kentleşmenin bir sonucu olarak kentsel doku önemli ölçüde değişirken, akademisyenler aynı zamanda, trafik sıkışıklığında, metropol alanlardaki kirlilikte, kamu hizmetlerinde azalmada ve altyapının eskimesinde bir artışa dikkat çekmişlerdir. Bu göstermektedir ki; arazi kullanım değişikliğinin toplum ve çevre üzerinde olumsuz etkileri olabilmektedir. Bu olumsuz etkiler kamu idareleri üzerinde çok büyük bir baskı oluşturmaktadır. Sürdürülebilir olmak için ve ekosistemlerin doğru işleyişi için, korunması veya sürdürülmesi gereken doğal unsurların ve kısıtlamaların yanı sıra kalkınma için kullanılabilecek kaynakların kısıtlamalarıyla birlikte belirlenmesi gerekmektedir. Bu nedenle, gelecekteki kentsel genişlemenin doğru tahminleri, sürdürülebilir büyüme ve çevrenin korunması için gereklidir. Birleşmiş Milletler (BM), kentleşmenin sürdürülebilirliğini tahmin etmek için Sürdürülebilir Kalkınma Hedefi 11.3.1 göstergesi olan “arazi tüketim oranının nüfus artış hızına oranı”nın kullanılmasını tavsiye etse de özellikle gelecekteki kentsel genişlemeyle ilgili olarak şehir düzeyinde hala yetersiz doğru tahminler ve değerlendirmeler mevcuttur. Sürdürülebilir Kalkınma Hedefleri çerçevesinde kentsel sürdürülebilir kalkınma hedeflerinin gerçekleştirilmesinin önündeki temel engel, önümüzdeki yıllarda kentleşme sürdürülebilirliğinin dinamiklerinin sınırlı anlaşılması olmuştur. Bu makale, kentsel kullanımlar için arazi kullanımı değişikliklerini incelemekte ve ayrıca seçilen örnek çalışma alanında, yani Türkiye'nin NUTS3 (istatistik için karasal birimlerin terminolojisi) bölgelerinde yani şehirler düzeyinde konut ve endüstriyel/ticari arazi kullanımlarının projeksiyonu için farklı yöntemler uygulamaktadır. Yoğunluk ölçümleri, trend ekstrapolasyonu ve regresyon analizi, arazi kullanımını tahmin etmek için kullanılan söz konusu istatistiksel yöntemlerdir. Bulgular, geçmiş değişiklikleri yansıtmak için seçilen metodolojileri kullanmanın önemli bir belirsizliğe yol açtığını göstermektedir. Doğrusal regresyon doğu, kuzey ve batı için en yüksek konut arazi kullanım değerlerini; yoğunluk ölçümü ise kuzeybatı ve güney bölgeleri için en yüksek değerleri tahmin etmiştir. Endüstriyel/ticari arazi kullanım talebine ilişkin en yüksek değerler doğu ve kuzey için doğrusal regresyon yöntemiyle, kuzeybatı, güney ve batı bölgeleri için ise doğrusal eğilim ekstrapolasyonu yöntemiyle tahmin edildi. Sonuçlar, seçilen değişkenlerdeki varyasyondan ve çalışma bölgesinin mekânsal organizasyonundan önemli ölçüde etkilenebilir. Bu nedenle, Türkiye'deki arazi kullanımı değişikliklerini tahmin etmek amaçlı kullanılabilecek en uygun modeli seçmek için gelecekteki bir araştırma odağı olarak doğrulama analizi temel olacaktır. Mevcut analizin sonuçları, Türkiye bölgesel bağlamında arazi yönetimi ve kentsel arazi kullanımının sürdürülebilir büyümesi için kamu idareleri ve yerel makamlar tarafından benimsenebilir.
Citation - WoS: 3
Citation - Scopus: 2
The Inter-Relationships of Territorial Quality of Life With Residential Expansion and Densification: A Case Study of Regions in EU Member Countries
(MDPI, 2024) Ustaoglu, Eda; Williams, Brendan
High-density urban development is promoted by both global and local policies in response to socio-economic and environmental challenges since it increases mobility of different land uses, decreases the need for traveling, encourages the use of more energy-efficient buildings and modes of transportation, and permits the sharing of scarce urban amenities. It is therefore argued that increased density and mixed-use development are expected to deliver positive outcomes in terms of contributing to three pillars (social, economic, and environmental domains) of sustainability in the subject themes. Territorial quality of life (TQL)-initially proposed by the ESPON Programme-is a composite indicator of the socio-economic and environmental well-being and life satisfaction of individuals living in an area. Understanding the role of urban density in TQL can provide an important input for urban planning debates addressing whether compact development can be promoted by referring to potential efficiencies in high-density, mixed land use and sustainable transport provisions. Alternatively, low-density suburban development is preferable due to its benefits of high per capita land use consumption (larger houses) for individual households given lower land prices. There is little empirical evidence on how TQL is shaped by high-density versus low-density urban forms. This paper investigates this topic through providing an approach to spatially map and examine the relationship between TQL, residential expansion, and densification processes in the so-called NUTS2 (nomenclature of terrestrial units for statistics) regions of European Union (EU) member countries. The relative importance of each TQL indicator was determined through the entropy weight method, where these indicators were aggregated through using the subject weights to obtain the overall TQL indicator. The spatial dynamics of TQL were examined and its relationship with residential expansion and densification processes was analysed to uncover whether the former or the latter process is positively associated with the TQL indicator within our study area. From our regression models, the residential expansion index is negatively related to the TQL indicator, implying that high levels of residential expansion can result in a reduction in overall quality of life in the regions if they are not supported by associated infrastructure and facility investments.
Citation - WoS: 5
Citation - Scopus: 5
Building Composite Indicators for the Territorial Quality of Life Assessment in European Regions: Combining Data Reduction and Alternative Weighting Techniques
(Springer, 2025) Ustaoglu, Eda; Lopez, Gloria Ortega; Gutierrez-Alcoba, Alejandro
Development of composite indicators is a challenging task given that sustainability indices are strongly dependent on how the sub-indicators are weighted. This is because relative indicator weights may significantly differ based on the chosen weighting methods used in the analysis. There is hardly any study that has paid attention to this issue so far. Therefore, this paper aims to fill this gap in the literature by searching the robustness of selected weighting methods, i.e. entropy-weight (EW), principal component analysis (PCA), machine learning approaches (random forest-RF), regression analysis (RA) and benefit-of-the-doubt (BOD) when constructing a composite indicator. To research the current sustainability performance of European regions, the present study focuses on the Territorial Quality of Life Index-initially proposed by the ESPON Programme-that are aligned with the specific targets of the Sustainable Development Goals of the 2030 Agenda. The methods to construct composite indicators include stages of data preparation (including the estimation of missing values with random forest method), normalization, statistical transformation of raw data, reduction of indicators in order to ease public communication (using the PCA method) and data interpretation, weighting of the sub-indicators using EW, PCA, RF, RA and BOD methods and their linear weighted aggregation, and checking for robustness and sensitivity. The results suggest that there are significant differences in the rank and spatial distribution of composite indicators based on the use of different weighting methods considered in the analysis. The results from sensitivity analysis support the robustness of entropy-weight method among others. The methodology used in the current analysis can be adapted to other study areas and regions internationally. The findings showed that Eastern European countries and some Mediterranean countries have relatively lower index values compared to other European regions; therefore, policy and planning actions are needed covering these regions specifically.
A Spatial Econometric Analysis of the Regional Variations of Residential Energy Consumption in Europe
(IGI Global, 2024) Ustaoglu, Eda
A residential energy consumption model was estimated by using socio-economic characteristics, economic activities, mobility, land cover, natural hazards, governance, energy, air quality, and green economy variables for the EU-27 and UK. Regional variations of the energy consumption were also investigated through focusing on European regional typologies including urban, intermediate, and rural regions. The residential energy consumption model was estimated by using spatial econometric approaches as well as specific regression models were estimated for the urban, intermediate, and rural regions. The key variables used in regression analysis were selected according to their importance using the Random Forest (RF) classification method. The results from the regressions confirm that socio-economic, environmental, governance, technology, and natural hazards related variables explain residential energy consumption in Europe. The variations of sign and coefficients of the variables according to different regional typologies were also uncovered. © 2024 Elsevier B.V., All rights reserved.
Citation - WoS: 14
Citation - Scopus: 19
Institutional Settings and Effects on Agricultural Land Conversion: A Global and Spatial Analysis of European Regions
(MDPI, 2023) Ustaoglu, Eda; Williams, Brendan
Spatial planning systems and institutions have a significant role in managing non-agricultural land growth in Europe and the assessment of how their implementation impacts on agricultural land consumption is of great significance for policy and institutional improvement. Reducing the area of agricultural land taken for urban development, or eliminating such conversion, is an international policy priority aiming to maintain the amount and quality of land resources currently available for food production and sustainable development. This study aimed to evaluate the impact of land use planning systems and institutional settings on urban conversion of agricultural land in the 265 NUTS2 level EU27 and UK regions. Taking these regions as the unit of our analysis, the research developed and used global and local econometrics models to estimate the effect based on socio-economic, institutional and land use data for the 2000-2018 period. There is limited research focusing on the impacts of institutional settings and planning types of the European countries on the conversion of agricultural land. Furthermore, existing research has not considered the spatial relationships with the determinants of agricultural land conversion and the response variable, therefore, our research aimed to contribute to the literature on the subject. The results showed that the types of spatial planning systems and institution variables significantly impact the conversion of agricultural land to urban uses. Socio-economic indicators and areas of agricultural and urban land have significant impact on agricultural land conversion for any type of spatial planning system. A further result was that decentralization and political fragmentation were positively associated with agricultural land conversion while quality of regional government and governance was negatively associated. A local regression model was assessed to explore the different spatial patterns of the relationships driving agricultural land conversion. The main empirical finding from this model was that there was spatial variation of driving factors of agricultural land conversion in Europe.
Examining the Impact of Landslide Hazards in the Periurban Areas by Global and Local Modelling Techniques
(IGI Global, 2024) Aydinoǧlu, Arif Çaǧdaş; Sisman, Suleyman; Ustaoglu, Eda; Aydogdu, Gehver
Landslides can be considered one of the most severe natural hazards globally, and their management has a key role to inman safety. Landslide susceptibility maps can help the sustainable management of peri-urban areas such as determining the target areas of projects to develop landslide resistant areas, forest planning, infrastructure planning, and land use zoning. This study aims to analyse the relationship between landslide occurrence and its determinants in a peri-urban region, namely Taslidere Basin located in Guneysu District of Rize, Turkey, through providing both global and local regression models. To consider spatial non-stationarity, geographically weighted regression was used as a local model. It was found that the local model outperformed the global model in the estimation of landslide susceptibility determinants. The spatial analysis results indicated that almost all variables had heterogeneous variation over the study area. Therefore, this study provides a methodology for understanding the local dynamics of landslide occurrence. © 2024 Elsevier B.V., All rights reserved.
Citation - Scopus: 2
Using Night-Time Lights and Statistical Data to Measure Regional Inequality in Turkey
(IGI Global, 2024) Ustaoglu, Eda
Poverty and inequality are the outstanding challenges in both developing and developed countries in the globe. Using Suomi National Polar-orbiting Partnership (NPP)-Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light (NTL) images and socio-economic data from administrative sources, this chapter focuses on the association between nighttime lights and economic activities with an aim of computing regional income inequality indices for the year 2015 in Turkey. Gini, the Atkinson and Theil statistics were used to establish regional inequality indices using both NTL and statistics data. The findings indicated that urban NTLs are strongly correlated with economic activity while the correlation is much weaker regarding rural nightlights and agricultural output. It can be noted that there was increasing regional inequality in north-west, south, and south-east regions whereas regional equality was more homogeneously distributed. The results indicated that NPP-VIIRS nightlight data can help to perform regional inequality assessments for the urban areas in Turkey. © 2024 Elsevier B.V., All rights reserved.