Unmanned aerial vehicles (UAV) have been used in a variety of fields in the last decade. In forestry, they have been used to estimate tree heights and crowns with different sensors. This approach, with a consumer-grade onboard system camera, is becoming popular because it is cheaper and faster than traditional photogrammetric methods and UAV-light detecting and ranging systems (UAV-LiDAR). In this study, UAV-based imagery reconstruction, processing, and local maximum filter methods are used to obtain individual tree heights from a coniferous urban forest. A low-cost onboard camera and a UAV with a 96-cm wingspan made it possible to acquire high resolution aerial images (6.41 cm average ground sampling distance), ortho-images, digital elevation models, and point clouds in one flight. Canopy height model, obtained by extracting the digital surface model from the digital terrain model, was filtered locally based on the pixel-based window size using the provided algorithm. For accuracy assessment, ground-based tree height measurements were made. There was a high 94% correlation and a root-mean-square error of 28 cm. This study highlights the accuracy of the method and compares favourably to more expensive methods.

En tr Climate is one of the most important factors that enable the existence of life on Earth. The climate has been studied by many scientists throughout the history for its influence on all living and non-living beings. Researchers have used climatological parameters (temperature, humidity, rainfall, sunshine duration, evapotranspiration etc.) with different approaches and created a variety of methods. When putting these classifications into consideration, they have taken different criteria into account and have produced different classification. Some of these formulas are short and simple, some are very long and complex. Using these formulas, researchers have determined different climatic types suited to different regions. In this study, two separate climate classification methods were used (Erinç and De Martonne). Meteorological data ranging from 1980 to 2011 were examined periodically and arranged according to determined classification methods. The data were processed in accordance with De Martonne and Erinç classification formulas by GIS and the climate change of İzmir province has been revealed between 1980-1989 and 2006-2011 time periods.
İklim dünya üzerinde yaşamın var olmasını sağlayan en önemli etkenlerden biridir. İklim, canlı ve cansız bütün varlıklar üzerindeki etkisinden dolayı tarih boyunca birçok bilim insanı tarafından incelenmiştir. Araştırmacılar iklimi oluşturan parametreleri (sıcaklık, yağış, nem güneşlenme süresi, rüzgâr, evapotranspirasyon vb.) farklı yöntemlerle birlikte kullanarak birçok iklim sınıflandırma yöntemleri ortaya koymuştur. Bu sınıflandırmaları ortaya koyarken farklı ölçütleri dikkate almışlar ve bu ölçütlere göre farklı sınıflandırma indisleri ortaya çıkarmışlardır. Sınıflandırmalarla alakalı birçok eşitlik mevcuttur. Bu eşitliklerin bir kısmı kısa ve basit, bir kısmı ise çok uzun ve karmaşıktır. Araştırmacılar bu eşitlikleri kullanarak farklı bölgelerde farklı iklim tipleri ortaya koymuşlardır. Bu çalışmada, Türkiye Meteoroloji Genel Müdürlüğü’nden elde edilen 1980-2011 arasındaki meteorolojik veriler dönemler halinde incelenmiş ve iki ayrı iklim sınıflandırma yöntemi kullanılarak belirlenen sınıflandırma yöntemlerine göre düzenlenmiştir. Düzenlenen veriler CBS ile De Martonne ve Erinç sınıflandırma eşitliklerine uygun şekilde işleme konulmuş ve çalışma alanı olarak seçilmiş olan İzmir ilinin 1980-1989 ve 2006-2011 yılları arasındaki iklim değişiklikleri tespit edilmiştir.

Climate change has become a significant concern globally, and understanding regional patterns and trends is crucial for effective mitigation and adaptation strategies. This article presents a comprehensive Mann–Kendall trend and Sen’s slope estimator test conducted to examine the long-term trends in surface temperature, 2-m above temperature, and precipitation in Sivas Province, Turkey. Utilizing a dataset spanning several decades, Mann–Kendall and Sen’s slope estimator tests were applied to assess the presence of statistically significant trends in the selected climatic parameters. Additionally, remote sensing (RS) and geographical information systems (GIS) were incorporated as supplementary and validation data sources to enhance the accuracy and reliability of our analysis. Furthermore, GIS techniques facilitated the integration of diverse geospatial data layers, including land cover, offering valuable insights into the complex interactions between climate variables and the environment. The combined analysis of MK trends, SS test, and RS/GIS data yielded a robust understanding of the changing climate dynamics in Sivas Province. Our findings not only contribute to the growing body of knowledge on regional climate change but also underscore the importance of utilizing advanced technologies like RS and GIS for accurate trend analysis and informed decision making. This study highlights the potential of these supplementary data sources in enhancing our understanding of climate trends and supports the development of climate change adaptation strategies.

The speedy progress of the global system for mobile communication services and the ensuing increased electromagnetic field (EMF) exposure to the human body have generated debate on the potential hazard with attentiveness to human health. The aim of this study is to provide a homogeneous distribution of electromagnetic field sources on our university campus and determine possible risk zones via the electromagnetic intensity maps drawn using the data to be obtained from the measurement results. It was determined how much electromagnetic intensity of the campus was under 4 different high frequencies (900, 1800, 2400, and 2600 MHz), which were determined using the geographic information system. Electromagnetic field measurements were performed at points where the topographic structure of the land allowed, at intervals of about 50 meters in the parts with building density inside the campus, and at intervals ranging between 100 and 120 meters in the open areas where there were no buildings, and geographical location information about the points where these measurements were made was specified with an accuracy of cm level. As a result, our measurement values are also below the limit values of the limit electromagnetic values determined by ICNIRP.

Climate change has become a significant concern globally, and understanding regional patterns and trends is crucial for effective mitigation and adaptation strategies. This article presents a comprehensive Mann-Kendall trend and Sen’s slope estimator test conducted to examine the long-term trends in surface temperature, 2-meter above temperature, and precipitation in Sivas Province, Turkey. Utilizing a dataset spanning several decades, Mann-Kendall and Sen’s slope estimator tests were applied to assess the presence of statistically significant trends in the selected climatic parameters. Additionally, Remote Sensing (RS) and Geographical Information Systems (GIS) were incorporated as supplementary and validation data sources to enhance the accuracy and reliability of our analysis. Furthermore, GIS techniques facilitated the integration of diverse geospatial data layers, including land cover, offering valuable insights into the complex interactions between climate variables and the environment. The combined analysis of MK trends, SS test and RS/GIS data yielded a robust understanding of the changing climate dynamics in Sivas Province. Our findings not only contribute to the growing body of knowledge on regional climate change but also underscore the importance of utilizing advanced technologies like RS and GIS for accurate trend analysis and informed decision-making. This study highlights the potential of these supplementary data sources in enhancing our understanding of climate trends and supports the development of climate change adaptation strategies.