Browsing by Author "Cabuk, Saye Nihan"

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Assessing the effects of wind farms on soil organic carbon.
(2021-04-01T00:00:00Z) Pekkan, Ozge Isik; Senyel Kurkcuoglu, Muzeyyen Anil; Cabuk, Saye Nihan; Aksoy, Talha; Yilmazel, Burcu; Kucukpehlivan, Tuncay; Dabanli, Ahmet; Cabuk, Alper; Cetin, Mehmet
Wind energy is considered one of the cleanest and most sustainable resources among renewable energy sources. However, several negative environmental impacts can be observed, unless suitable sites are selected for the establishment of wind farms. The aim of this study is to determine the change in the soil organic carbon (SOC) stock resulting from land cover changes that were caused by wind farm establishments in the Karaburun peninsula. Within the scope of the study, remote sensing and geographic information system technologies were utilized. Maximum likelihood algorithm, one of the supervised classification techniques, was used to classify the land cover, and Normalized Difference Vegetation Index (NDVI) analyses were performed to determine land cover changes. The findings were correlated with the "Turkey Soil Organic Carbon Project" data. As a result, depending on the establishment of wind farms in the Karaburun Peninsula, a total decrease of 18,330.57 tons of SOC in the study area between 2000 and 2019 was determined. It should be taken into consideration that besides many other negative effects (effects on human health, effects on the ecosystem, effects on animals, etc.), land cover changes caused by wind farms may indirectly cause important problems such as climate change. Recently, this situation shows that there is an important dilemma in terms of current implementations. Wind farms are the most invested renewable energy sources and alternative energy supply to fossil fuels in terms of preventing climate change. However, the results of this study have reviewed that lack of proper approaches and methods to establish wind farms may result in various problems such as physical, chemical, and biological degradations and an increase in the amount of atmospheric carbon. Consequently, the investments in renewable energy sources should be comprehensively reevaluated in terms of current technologies, quality in the scope of environmental impact assessment and strategic environmental assessment processes, legal regulations and national policies, long-term environmental costs, etc.
Development of forest fire risk map using geographical information systems and remote sensing capabilities: Ören case.
(2021-02-27T00:00:00Z) Ozenen Kavlak, Mehtap; Cabuk, Saye Nihan; Cetin, Mehmet
Forest fires globally cause severe losses in vegetation, soil and habitats and inevitably have direct and indirect negative environmental impacts such as deforestation, climate change and drought. According to the official records, there has been an increase of 58% in the number of the forest fires in Turkey in the last 30 years, between 1988 and 2018. Therefore, it is vital to determine the forest fire risks in the country and develop more effective methodologies to mitigate them. From this point, in the first phase, forest fire risk map of Kütahya-Ören region was prepared via the analyses of a variety of spatial data using geographical information system capabilities. The visibility analysis for the current fire towers was also performed. The results showed that very-high and high-risk, moderate-risk and low-risk zones respectively comprised 36.86%, 60.39% and 2.76% of the total study area, and 82.8% of the region was visible from the towers. In the second phase of the study, remote sensing methods were utilized for the detection of the areas burned in October 2001 in Ören-Çamdibi region, which was officially recorded as 4 hectares. The results revealed that the actual amount of the burned area was 5.6 hectares, and 83% of the burned surfaces was classified as moderate-risk areas in the fire risk map, while 17% of it was that of very-high and high-risk zones.
Estimation of the water footprint of kiwifruit: in the areas transferred from hazelnut to kiwi.
(2022-10-01T00:00:00Z) Bilge Ozturk, Gulsah; Ozenen Kavlak, Mehtap; Cabuk, Saye Nihan; Cabuk, Alper; Cetin, Mehmet
Agriculture is the largest consumer of freshwater and plays a critical role in addressing global water scarcity. While numerous studies have focused on the water footprint (WF) of various agricultural products, little attention has been paid to changing cropping patterns and their impact on WF. Here, we investigate the impact of conversion from hazelnut fields to kiwi orchards on green, blue, and gray WF between 2010 and 2021 in Ordu, Turkey. Our results show a total increase of 803,901 tons WF for all green, blue, and gray WF. Compared to the previous situation, changing the agricultural product and growing kiwifruit on previously established hazelnut fields increases green WF by 372,106 tons and blue WF by 334,167 tons. Thus, the change of cultivation pattern could significantly contribute to the water scarcity in the area, and at the same time, the increase in WF. Although kiwi cultivation might be advantageous economically, this economic benefit might be an ecological disadvantage as kiwi production is highly dependent on limited blue water resources. Therefore, it is suggested to further promote the rain-fed product, the hazelnut.
Evaluation of comparing urban area land use change with Urban Atlas and CORINE data.
(2022-04-01T00:00:00Z) Aksoy, Talha; Dabanli, Ahmet; Cetin, Mehmet; Senyel Kurkcuoglu, Muzeyyen Anil; Cengiz, Adem Emre; Cabuk, Saye Nihan; Agacsapan, Balca; Cabuk, Alper
Urban Atlas (UA) data covering the large urban areas have been produced by the European Environment Agency for a variety of European countries including Turkey since 2006. The use of the UA data for the determination of spatiotemporal land use and density changes in urban areas. UA data of Eskisehir, Turkey, were used in order to detect the spatiotemporal changes between 2012 and 2018. CORINE data-based change detection and NDVI analysis were also made and compared with the results obtained from the UA data. The results based on the UA data revealed that the artificial surfaces in the study area increased by 17.65% and there was a 18.32% increase in the total amount of agricultural lands, natural lands, forests, and vegetation. Although CORINE data-based analyses showed a similar trend in land use/land cover changes, the amount of changes between 2012 and 2018 in CORINE and UA data-based analyses were found to be 4.99% and 17.55%, respectively. A 9.30% mismatch between the UA changes and NDVI difference data was also calculated. Research findings revealed that the utilization of the UA data in the urban territories would be advantageous especially in planning processes to detect and compare the changes in the artificial and non-artificial surfaces and NDVI analysis would be very supportive to control and compare the results. It is also concluded that this study may be a useful model to monitor the cities in accordance with the 2030 and 2050 policies of European Council on Land Use, Land Use Change and Forestry.
The change detection in coastal settlements using image processing techniques: a case study of Korfez.
(2022-02-01T00:00:00Z) Sahin, Gulenay; Cabuk, Saye Nihan; Cetin, Mehmet
Coastal areas all over the world are usually exposed to intensive change and transformation processes resulting in a variety of natural, physical, and socio-economic problems. Körfez province, located along the İzmit Bay of Marmara Sea, Turkey, has been one of these coastal areas that has become a major point for industrial facilities and highly populated urbanized area since 1960s. Therefore, the analysis of the spatial changes in the land use patterns of the province has a critical role in the success of the physical planning processes and the protection of the coastal areas. In order to highlight this critical role, temporal change detection analysis for Körfez province covering a 6-year period and 5 land use classes was made using 2009 and 2015 SPOT imagery and thematic maps. Reclassified CORINE data, development plans, and land survey results were benefited for the supervised classification of the images. Four hundred eighty control points for each year were used to achieve a strong accuracy tested by Kappa coefficient. The spatio-temporal change detection results revealed a 22.5% and 2.3% decrease in agricultural lands and sea areas respectively, while there was an increase of 16.6% in forest-green areas, 6.4% in settlement areas, and 74.1% in lake areas. The results are believed to be significant input data to facilitate coastal and physical development planning over the area, and thus make sustainable land use decisions to protect the delicate landscape and coastal characteristics, while providing a sound risk management plan.