{"title":"A Model on Charter Rate Prediction in Container Shipping","authors":"Tolga TUZCUOĞLU, Hüseyin GENCER","doi":"10.30897/ijegeo.1345053","DOIUrl":"https://doi.org/10.30897/ijegeo.1345053","url":null,"abstract":"The maritime industry has witnessed numerous challenges in recent years after the global pandemic, primarily characterized by sharp fluctuations in the daily charter rates. Considering an unpredictable business environment, this study aims to suggest a financial forecasting model on charter rates, creating added value for the stakeholders of the maritime trade business. The empirical analysis utilized the data from the Clarksons Research Portal, which encompassed 7,409 charter rental transactions of container ships from 01.01.2018 to 10.03.2023. After examining seven different linear and ensemble regressions, it was revealed that the XGBoost regressor resulted in the least RMSE value of 0.1833 with an R2 of 0.9015. The selected predictors were the TEU, container fixture type, charter time, charter time multiplied by TEU, ship age, laycan year, and laycan month, respectively. In addition to coping with the limitations of linear regression, the model revealed that the laycan years, charter time, and charter time multiplied with TEU were the essential variables in charter rate prediction. As a result, the model developed in the study can be used as an important decision support tool for stakeholders in the container shipping industry.","PeriodicalId":492501,"journal":{"name":"International journal of environment and geoinformatics","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136278766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Antibiotic and Heavy Metal Resistance Patterns of Indicator Bacteria in Surface Water Bodies of Kilis","authors":"Hatice Aysun MERCİMEK TAKCI, Sevil TOPLAR","doi":"10.30897/ijegeo.1276211","DOIUrl":"https://doi.org/10.30897/ijegeo.1276211","url":null,"abstract":"The surface waters contaminated with coliform bacteria having antibiotic and heavy metal resistance have become an increasing public health risk. For this reason, it is aimed to detect the bacterial quality, the frequency of antibiotics, heavy metal resistance, and bioindicator bacteria in surface water sources taken from Kilis. The resistance profile of sixteen bacteria species belonging to class Gammaproteobacteria to standard antibiotics and heavy metal salts was investigated using Kirby-Bauer disc diffusion techniques. The various physicochemical parameters such as total dissolved solids (TDS), electrical conductivity (EC), pH, temperature, dissolved oxygen amount, and biochemical oxygen demand (BOD) of samples were also examined. The total coliform load was recorded as˃1100 (MPN)/100 mL and calculated comparatively lower values (53(MPN)/100 mL) of fecal contamination for both stations. A high level of resistance to clindamycin in a total of 16 strains was observed. Ampicillin (56.25%), cefotaxime (37.5%), and ceftazidime (31.25%) followed them. The trends in heavy metal resistance of isolates increased in the order of Cd2+< Pb2+","PeriodicalId":492501,"journal":{"name":"International journal of environment and geoinformatics","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136271475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Effects of Green Spaces on Microclimate in Sustainable Urban Planning","authors":"Fatih ADIGÜZEL","doi":"10.30897/ijegeo.1342287","DOIUrl":"https://doi.org/10.30897/ijegeo.1342287","url":null,"abstract":"In recent years, there has been a growing importance placed on the development of various models and scenarios aimed at mitigating the effects of climate change. This approach is gaining prominence in our country as well. This study is based on research conducted in the Yeşilyurt neighborhood within the Tarsus district of Mersin province. The primary objective of this research is to assess the impact of increased green space on microclimate conditions using ENVI-met simulation. Within the scope of this research, a comparison was made between the current situation and a scenario in which the amount of green space was increased. The analysis of green area quantities was conducted using the ENVI-met simulation software, utilizing climate data such as temperature, humidity, wind direction, and speed, which were obtained through measurements. In the scenario involving an increase in green space, the total green area was augmented from its current 2,487 m² to 4,398 m². The simulation results underscore the substantial effect of this augmentation on the microclimate. Average temperature values fluctuate between 31.11°C and 33.04°C, revealing that the expansion of green space leads to a reduction in temperature, thereby positively impacting the environment. This translates to an overall temperature decrease of approximately 0.45°C across the entire area. The research highlights the favorable influence of heightened green space on microclimate conditions, as evidenced by findings derived from ENVI-met simulations. It elucidates how such an increase can contribute to temperature regulation. These outcomes underscore the significance of deliberate green space incorporation in urban planning and design processes, guiding decisions that promote environmental sustainability. Thus, it is recommended that forthcoming strategies of local governments prioritize the expansion of green areas while considering factors related to microclimate and environmental quality.","PeriodicalId":492501,"journal":{"name":"International journal of environment and geoinformatics","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136271915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Rainwater Storage Engineering based on Water-Sensitive Urban Design in Lapangan Pancasila, Semarang City","authors":"Qatrunnada Justitia YUMNA, Pingkan NURYANTİ","doi":"10.30897/ijegeo.1233028","DOIUrl":"https://doi.org/10.30897/ijegeo.1233028","url":null,"abstract":"Lapangan Pancasila is a public open space that located in Jln. Seroja Dalam III no. 9 Semarang City. Flooding is often occurs at Lapangan Pancasila in rainy season. Floods in Semarang City are caused by the occurrence of land subsidence and water catchment area decreases. Rainwater harvesting system with water sensitive urban design(WSUD) basic, is one of plenty solution that can be applied to reduces flooding at Lapangan Pancasila. The research was conducted using a descriptive methodology which refers to the spatial and ecological approach. A spatial approach is used to determine the physical condition of the site, while an ecological approach is used to determine the components required for engineering rainwater storage. Based on the calculations that have been carried out, the discharge from the calculation of the planned rainfall is 0.003886 m3/s. Rainwater collection engineering at Lapangan Pancasila was built as a complex system that combines various components of rainwater treatment such as rainwater catchment areas, macro water filtration tanks, sand filter tanks to filter mud and purify water, clean water reservoirs, sprinkle landscape irrigation systems, and infiltration wells.","PeriodicalId":492501,"journal":{"name":"International journal of environment and geoinformatics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136272068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ömer Faruk ATİZ, Tansu ALKAN, Süleyman Savaş DURDURAN
{"title":"Google Earth Engine Based Spatio-Temporal Changes of Bafa Lake from 1984 to 2022","authors":"Ömer Faruk ATİZ, Tansu ALKAN, Süleyman Savaş DURDURAN","doi":"10.30897/ijegeo.1257413","DOIUrl":"https://doi.org/10.30897/ijegeo.1257413","url":null,"abstract":"The water resource management is crucial to protect environment and ecological cycle. The detection of temporal and spatial changes in the lake's water extent is important for sustainable land planning. Therefore, the areal changes over the wetlands must be well monitored. Bafa Lake is an essential downstream water in the Büyük Menderes Basin which is the largest river basin of the Aegean Region. Google Earth Engine (GEE) is an easy-to-use online remote sensing data processing platform based on cloud computing. In this study, the long-term spatio-temporal changes of Bafa Lake between 1984-2022 have been analyzed using Landsat-5/8 satellite images on the GEE platform. A total of 1093 Landsat images were processed. The annual water areas were computed through composite images per year. The water area extraction was done using the normalized water difference index (NDWI). The minimum and maximum lake water areas in 38 years were detected as 5474 ha and 6789 ha in 1990 and 2006, respectively. In the accuracy assessment according to random sampling points, the Overall Accuracy (OA) was calculated as 98% and the kappa coefficient as 0.96. The water surface area was increased by 3.9% from 1984 to 2022. Between 2015-2022, the maximum increase or decrease in the lake area compared to the previous year observed as less than 1%. Therefore, there has not been a notable variation in the water area of Bafa Lake in the past few years.","PeriodicalId":492501,"journal":{"name":"International journal of environment and geoinformatics","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136272072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}